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A Closer Look at Spatiotemporal Convolutions for Action Recognition | 2,480 | cvpr | 162 | 28 | 2023-06-03 02:03:24.133000 | https://github.com/facebookresearch/R2Plus1D | 1,020 | A closer look at spatiotemporal convolutions for action recognition | https://scholar.google.com/scholar?cluster=9524036545693727210&hl=en&as_sdt=0,33 | 111 | 2,018 |
SurfConv: Bridging 3D and 2D Convolution for RGBD Images | 22 | cvpr | 6 | 0 | 2023-06-03 02:03:24.333000 | https://github.com/chuhang/SurfConv | 53 | Surfconv: Bridging 3d and 2d convolution for rgbd images | https://scholar.google.com/scholar?cluster=7050444684028736511&hl=en&as_sdt=0,33 | 4 | 2,018 |
Efficient Video Object Segmentation via Network Modulation | 344 | cvpr | 24 | 5 | 2023-06-03 02:03:24.532000 | https://github.com/linjieyangsc/video_seg | 152 | Efficient video object segmentation via network modulation | https://scholar.google.com/scholar?cluster=1976126252599424631&hl=en&as_sdt=0,33 | 7 | 2,018 |
Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment | 170 | cvpr | 12 | 1 | 2023-06-03 02:03:24.732000 | https://github.com/ld-ing/TCFPN-ISBA | 40 | Weakly-supervised action segmentation with iterative soft boundary assignment | https://scholar.google.com/scholar?cluster=8585781658332698642&hl=en&as_sdt=0,44 | 4 | 2,018 |
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet? | 1,749 | cvpr | 911 | 153 | 2023-06-03 02:03:24.932000 | https://github.com/kenshohara/3D-ResNets-PyTorch | 3,611 | Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet? | https://scholar.google.com/scholar?cluster=4579944187863414163&hl=en&as_sdt=0,22 | 59 | 2,018 |
PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection | 759 | cvpr | 16 | 0 | 2023-06-03 02:03:25.132000 | https://github.com/nian-liu/PiCANet | 34 | Picanet: Learning pixel-wise contextual attention for saliency detection | https://scholar.google.com/scholar?cluster=10105062679755015166&hl=en&as_sdt=0,5 | 5 | 2,018 |
What Do Deep Networks Like to See? | 36 | cvpr | 3 | 0 | 2023-06-03 02:03:25.333000 | https://github.com/spalaciob/s2snets-reconstruction | 14 | What do deep networks like to see? | https://scholar.google.com/scholar?cluster=5407091813991175051&hl=en&as_sdt=0,33 | 2 | 2,018 |
Multi-Frame Quality Enhancement for Compressed Video | 194 | cvpr | 21 | 2 | 2023-06-03 02:03:25.532000 | https://github.com/ryangBUAA/MFQE | 92 | Multi-frame quality enhancement for compressed video | https://scholar.google.com/scholar?cluster=13441933018643229678&hl=en&as_sdt=0,5 | 6 | 2,018 |
Active Fixation Control to Predict Saccade Sequences | 41 | cvpr | 1 | 1 | 2023-06-03 02:03:25.732000 | https://github.com/TsotsosLab/STAR-FC | 16 | Active fixation control to predict saccade sequences | https://scholar.google.com/scholar?cluster=5313953482186601173&hl=en&as_sdt=0,14 | 8 | 2,018 |
Latent RANSAC | 30 | cvpr | 10 | 0 | 2023-06-03 02:03:25.932000 | https://github.com/rlit/LatentRANSAC | 23 | Latent ransac | https://scholar.google.com/scholar?cluster=16432006796453756987&hl=en&as_sdt=0,47 | 8 | 2,018 |
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation | 476 | cvpr | 50 | 11 | 2023-06-03 02:03:26.133000 | https://github.com/yhjo09/VSR-DUF | 217 | Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation | https://scholar.google.com/scholar?cluster=14547343431451944570&hl=en&as_sdt=0,1 | 10 | 2,018 |
Learning a Single Convolutional Super-Resolution Network for Multiple Degradations | 860 | cvpr | 78 | 19 | 2023-06-03 02:03:26.333000 | https://github.com/cszn/SRMD | 403 | Learning a single convolutional super-resolution network for multiple degradations | https://scholar.google.com/scholar?cluster=12748399699451058322&hl=en&as_sdt=0,5 | 13 | 2,018 |
FFNet: Video Fast-Forwarding via Reinforcement Learning | 53 | cvpr | 4 | 1 | 2023-06-03 02:03:26.534000 | https://github.com/shuyueL/FFNet | 20 | Ffnet: Video fast-forwarding via reinforcement learning | https://scholar.google.com/scholar?cluster=12600528794155457319&hl=en&as_sdt=0,34 | 1 | 2,018 |
Domain Adaptive Faster R-CNN for Object Detection in the Wild | 1,042 | cvpr | 69 | 13 | 2023-06-03 02:03:26.734000 | https://github.com/yuhuayc/da-faster-rcnn | 320 | Domain adaptive faster r-cnn for object detection in the wild | https://scholar.google.com/scholar?cluster=2169991804006218555&hl=en&as_sdt=0,5 | 11 | 2,018 |
Low-Shot Learning With Large-Scale Diffusion | 116 | cvpr | 5 | 0 | 2023-06-03 02:03:26.935000 | https://github.com/facebookresearch/low-shot-with-diffusion | 47 | Low-shot learning with large-scale diffusion | https://scholar.google.com/scholar?cluster=18181091707667282501&hl=en&as_sdt=0,5 | 7 | 2,018 |
Referring Relationships | 94 | cvpr | 81 | 10 | 2023-06-03 02:03:27.136000 | https://github.com/StanfordVL/ReferringRelationships | 262 | Referring relationships | https://scholar.google.com/scholar?cluster=6942937541363789656&hl=en&as_sdt=0,33 | 19 | 2,018 |
Adversarially Learned One-Class Classifier for Novelty Detection | 617 | cvpr | 77 | 0 | 2023-06-03 02:03:27.336000 | https://github.com/khalooei/ALOCC-CVPR2018 | 204 | Adversarially learned one-class classifier for novelty detection | https://scholar.google.com/scholar?cluster=13603058643518336613&hl=en&as_sdt=0,48 | 16 | 2,018 |
Improving Object Localization With Fitness NMS and Bounded IoU Loss | 189 | cvpr | 29 | 4 | 2023-06-03 02:03:27.537000 | https://github.com/lachlants/denet | 112 | Improving object localization with fitness nms and bounded iou loss | https://scholar.google.com/scholar?cluster=10163124065967812010&hl=en&as_sdt=0,10 | 11 | 2,018 |
End-to-End Deep Kronecker-Product Matching for Person Re-Identification | 148 | cvpr | 29 | 1 | 2023-06-03 02:03:27.739000 | https://github.com/YantaoShen/kpm_rw_person_reid | 103 | End-to-end deep kronecker-product matching for person re-identification | https://scholar.google.com/scholar?cluster=4096787433309580582&hl=en&as_sdt=0,5 | 6 | 2,018 |
Deformable GANs for Pose-Based Human Image Generation | 443 | cvpr | 81 | 21 | 2023-06-03 02:03:27.940000 | https://github.com/AliaksandrSiarohin/pose-gan | 373 | Deformable gans for pose-based human image generation | https://scholar.google.com/scholar?cluster=3043558815618961635&hl=en&as_sdt=0,5 | 18 | 2,018 |
Deep Reinforcement Learning of Region Proposal Networks for Object Detection | 73 | cvpr | 19 | 0 | 2023-06-03 02:03:28.139000 | https://github.com/aleksispi/drl-rpn-tf | 72 | Deep reinforcement learning of region proposal networks for object detection | https://scholar.google.com/scholar?cluster=5027202690407581149&hl=en&as_sdt=0,5 | 6 | 2,018 |
Discriminability Objective for Training Descriptive Captions | 189 | cvpr | 22 | 7 | 2023-06-03 02:03:28.340000 | https://github.com/ruotianluo/DiscCaptioning | 110 | Discriminability objective for training descriptive captions | https://scholar.google.com/scholar?cluster=4573642077602787213&hl=en&as_sdt=0,10 | 6 | 2,018 |
Robust Classification With Convolutional Prototype Learning | 227 | cvpr | 32 | 4 | 2023-06-03 02:03:28.540000 | https://github.com/YangHM/Convolutional-Prototype-Learning | 117 | Robust classification with convolutional prototype learning | https://scholar.google.com/scholar?cluster=15165539618467322604&hl=en&as_sdt=0,44 | 7 | 2,018 |
Generative Modeling Using the Sliced Wasserstein Distance | 190 | cvpr | 3 | 2 | 2023-06-03 02:03:28.740000 | https://github.com/ishansd/swg | 33 | Generative modeling using the sliced wasserstein distance | https://scholar.google.com/scholar?cluster=16060361472863218540&hl=en&as_sdt=0,44 | 4 | 2,018 |
Learning Time/Memory-Efficient Deep Architectures With Budgeted Super Networks | 96 | cvpr | 5 | 0 | 2023-06-03 02:03:28.941000 | https://github.com/TomVeniat/bsn | 26 | Learning time/memory-efficient deep architectures with budgeted super networks | https://scholar.google.com/scholar?cluster=5514870632955712695&hl=en&as_sdt=0,33 | 3 | 2,018 |
Cross-View Image Synthesis Using Conditional GANs | 153 | cvpr | 11 | 8 | 2023-06-03 02:03:29.141000 | https://github.com/kregmi/cross-view-image-synthesis | 50 | Cross-view image synthesis using conditional gans | https://scholar.google.com/scholar?cluster=15120435124755343968&hl=en&as_sdt=0,34 | 4 | 2,018 |
Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing | 516 | cvpr | 36 | 15 | 2023-06-03 02:03:29.340000 | https://github.com/speedinghzl/DSRG | 245 | Weakly-supervised semantic segmentation network with deep seeded region growing | https://scholar.google.com/scholar?cluster=11401463134094123362&hl=en&as_sdt=0,39 | 12 | 2,018 |
Deep Spatial Feature Reconstruction for Partial Person Re-Identification: Alignment-Free Approach | 265 | cvpr | 31 | 9 | 2023-06-03 02:03:29.541000 | https://github.com/lingxiao-he/Partial-Person-ReID | 160 | Deep spatial feature reconstruction for partial person re-identification: Alignment-free approach | https://scholar.google.com/scholar?cluster=16383414441740542927&hl=en&as_sdt=0,5 | 7 | 2,018 |
Cascaded Pyramid Network for Multi-Person Pose Estimation | 1,245 | cvpr | 201 | 43 | 2023-06-03 02:03:29.743000 | https://github.com/chenyilun95/tf-cpn | 788 | Cascaded pyramid network for multi-person pose estimation | https://scholar.google.com/scholar?cluster=5670760275903596839&hl=en&as_sdt=0,33 | 27 | 2,018 |
Finding Task-Relevant Features for Few-Shot Learning by Category Traversal | 324 | cvpr | 31 | 6 | 2023-06-03 02:17:46.966000 | https://github.com/Clarifai/few-shot-ctm | 152 | Finding task-relevant features for few-shot learning by category traversal | https://scholar.google.com/scholar?cluster=7690321196923369761&hl=en&as_sdt=0,5 | 25 | 2,019 |
Edge-Labeling Graph Neural Network for Few-Shot Learning | 442 | cvpr | 65 | 21 | 2023-06-03 02:17:47.165000 | https://github.com/khy0809/fewshot-egnn | 260 | Edge-labeling graph neural network for few-shot learning | https://scholar.google.com/scholar?cluster=8574108187034418609&hl=en&as_sdt=0,36 | 6 | 2,019 |
Learning Video Representations From Correspondence Proposals | 66 | cvpr | 12 | 1 | 2023-06-03 02:17:47.364000 | https://github.com/xingyul/cpnet | 93 | Learning video representations from correspondence proposals | https://scholar.google.com/scholar?cluster=7665702673430883055&hl=en&as_sdt=0,34 | 1 | 2,019 |
Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning From Radiology Reports and Label Ontology | 57 | cvpr | 188 | 17 | 2023-06-03 02:17:47.564000 | https://github.com/rsummers11/CADLab | 409 | Holistic and comprehensive annotation of clinically significant findings on diverse CT images: learning from radiology reports and label ontology | https://scholar.google.com/scholar?cluster=6878217630382772571&hl=en&as_sdt=0,6 | 29 | 2,019 |
Generating Classification Weights With GNN Denoising Autoencoders for Few-Shot Learning | 251 | cvpr | 21 | 12 | 2023-06-03 02:17:47.764000 | https://github.com/gidariss/wDAE_GNN_FewShot | 148 | Generating classification weights with gnn denoising autoencoders for few-shot learning | https://scholar.google.com/scholar?cluster=13700723211966973086&hl=en&as_sdt=0,5 | 13 | 2,019 |
Kervolutional Neural Networks | 74 | cvpr | 3 | 4 | 2023-06-03 02:17:47.964000 | https://github.com/wang-chen/kervolution | 37 | Kervolutional neural networks | https://scholar.google.com/scholar?cluster=11581113643161028532&hl=en&as_sdt=0,33 | 7 | 2,019 |
Sphere Generative Adversarial Network Based on Geometric Moment Matching | 38 | cvpr | 4 | 1 | 2023-06-03 02:17:48.164000 | https://github.com/pswkiki/SphereGAN | 14 | Sphere generative adversarial network based on geometric moment matching | https://scholar.google.com/scholar?cluster=7334963438871902572&hl=en&as_sdt=0,33 | 0 | 2,019 |
Data Augmentation Using Learned Transformations for One-Shot Medical Image Segmentation | 399 | cvpr | 93 | 10 | 2023-06-03 02:17:48.363000 | https://github.com/xamyzhao/brainstorm | 389 | Data augmentation using learned transformations for one-shot medical image segmentation | https://scholar.google.com/scholar?cluster=15710438805315912771&hl=en&as_sdt=0,6 | 12 | 2,019 |
Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem | 409 | cvpr | 21 | 1 | 2023-06-03 02:17:48.563000 | https://github.com/max-andr/relu_networks_overconfident | 181 | Why relu networks yield high-confidence predictions far away from the training data and how to mitigate the problem | https://scholar.google.com/scholar?cluster=1495531200128833945&hl=en&as_sdt=0,1 | 6 | 2,019 |
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks | 505 | cvpr | 22 | 4 | 2023-06-03 02:17:48.763000 | https://github.com/dongyp13/Translation-Invariant-Attacks | 124 | Evading defenses to transferable adversarial examples by translation-invariant attacks | https://scholar.google.com/scholar?cluster=165426210106722967&hl=en&as_sdt=0,33 | 3 | 2,019 |
Hardness-Aware Deep Metric Learning | 176 | cvpr | 29 | 6 | 2023-06-03 02:17:48.963000 | https://github.com/wzzheng/HDML | 149 | Hardness-aware deep metric learning | https://scholar.google.com/scholar?cluster=8375662549135355127&hl=en&as_sdt=0,33 | 4 | 2,019 |
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation | 969 | cvpr | 46,274 | 1,204 | 2023-06-03 02:17:49.162000 | https://github.com/tensorflow/models | 75,883 | Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation | https://scholar.google.com/scholar?cluster=548023770660590636&hl=en&as_sdt=0,14 | 2,774 | 2,019 |
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration | 956 | cvpr | 107 | 12 | 2023-06-03 02:17:49.362000 | https://github.com/he-y/filter-pruning-geometric-median | 477 | Filter pruning via geometric median for deep convolutional neural networks acceleration | https://scholar.google.com/scholar?cluster=3978996322124428221&hl=en&as_sdt=0,22 | 7 | 2,019 |
Content Authentication for Neural Imaging Pipelines: End-To-End Optimization of Photo Provenance in Complex Distribution Channels | 13 | cvpr | 30 | 4 | 2023-06-03 02:17:49.561000 | https://github.com/pkorus/neural-imaging | 136 | Content authentication for neural imaging pipelines: End-to-end optimization of photo provenance in complex distribution channels | https://scholar.google.com/scholar?cluster=11213241954859682918&hl=en&as_sdt=0,5 | 11 | 2,019 |
DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds | 60 | cvpr | 46 | 0 | 2023-06-03 02:17:49.761000 | https://github.com/ai4ce/DeepMapping | 190 | DeepMapping: Unsupervised map estimation from multiple point clouds | https://scholar.google.com/scholar?cluster=9988954344653969501&hl=en&as_sdt=0,11 | 21 | 2,019 |
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans | 359 | cvpr | 75 | 13 | 2023-06-03 02:17:49.961000 | https://github.com/Sekunde/3D-SIS | 360 | 3d-sis: 3d semantic instance segmentation of rgb-d scans | https://scholar.google.com/scholar?cluster=18028162509439004162&hl=en&as_sdt=0,45 | 21 | 2,019 |
Image Deformation Meta-Networks for One-Shot Learning | 206 | cvpr | 7 | 3 | 2023-06-03 02:17:50.161000 | https://github.com/tankche1/IDeMe-Net | 49 | Image deformation meta-networks for one-shot learning | https://scholar.google.com/scholar?cluster=8511386292870768575&hl=en&as_sdt=0,1 | 3 | 2,019 |
GA-Net: Guided Aggregation Net for End-To-End Stereo Matching | 554 | cvpr | 136 | 30 | 2023-06-03 02:17:50.361000 | https://github.com/feihuzhang/GANet | 507 | Ga-net: Guided aggregation net for end-to-end stereo matching | https://scholar.google.com/scholar?cluster=731989336931762383&hl=en&as_sdt=0,49 | 26 | 2,019 |
Real-Time Self-Adaptive Deep Stereo | 233 | cvpr | 73 | 19 | 2023-06-03 02:17:50.561000 | https://github.com/CVLAB-Unibo/Real-time-self-adaptive-deep-stereo | 405 | Real-time self-adaptive deep stereo | https://scholar.google.com/scholar?cluster=18225618983635239070&hl=en&as_sdt=0,43 | 26 | 2,019 |
Occupancy Networks: Learning 3D Reconstruction in Function Space | 1,770 | cvpr | 254 | 75 | 2023-06-03 02:17:50.761000 | https://github.com/LMescheder/Occupancy-Networks | 1,197 | Occupancy networks: Learning 3d reconstruction in function space | https://scholar.google.com/scholar?cluster=14064961512731216993&hl=en&as_sdt=0,33 | 30 | 2,019 |
Detailed Human Shape Estimation From a Single Image by Hierarchical Mesh Deformation | 120 | cvpr | 47 | 4 | 2023-06-03 02:17:50.961000 | https://github.com/zhuhao-nju/hmd | 265 | Detailed human shape estimation from a single image by hierarchical mesh deformation | https://scholar.google.com/scholar?cluster=1439227329003947447&hl=en&as_sdt=0,33 | 15 | 2,019 |
Self-Calibrating Deep Photometric Stereo Networks | 116 | cvpr | 29 | 0 | 2023-06-03 02:17:51.161000 | https://github.com/guanyingc/SDPS-Net | 155 | Self-calibrating deep photometric stereo networks | https://scholar.google.com/scholar?cluster=3649234197372500195&hl=en&as_sdt=0,5 | 11 | 2,019 |
Argoverse: 3D Tracking and Forecasting With Rich Maps | 865 | cvpr | 211 | 49 | 2023-06-03 02:17:51.361000 | https://github.com/argoai/argoverse-api | 720 | Argoverse: 3d tracking and forecasting with rich maps | https://scholar.google.com/scholar?cluster=17363497644081299357&hl=en&as_sdt=0,44 | 28 | 2,019 |
Timeception for Complex Action Recognition | 193 | cvpr | 35 | 5 | 2023-06-03 02:17:51.562000 | https://github.com/noureldien/timeception | 158 | Timeception for complex action recognition | https://scholar.google.com/scholar?cluster=1175087663521850723&hl=en&as_sdt=0,11 | 8 | 2,019 |
Extreme Relative Pose Estimation for RGB-D Scans via Scene Completion | 35 | cvpr | 17 | 1 | 2023-06-03 02:17:51.762000 | https://github.com/zhenpeiyang/RelativePose | 147 | Extreme relative pose estimation for rgb-d scans via scene completion | https://scholar.google.com/scholar?cluster=9221764684170544668&hl=en&as_sdt=0,33 | 7 | 2,019 |
Long-Term Feature Banks for Detailed Video Understanding | 436 | cvpr | 67 | 15 | 2023-06-03 02:17:51.962000 | https://github.com/facebookresearch/video-long-term-feature-banks | 364 | Long-term feature banks for detailed video understanding | https://scholar.google.com/scholar?cluster=12076206268409002970&hl=en&as_sdt=0,48 | 11 | 2,019 |
IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition | 199 | cvpr | 40 | 7 | 2023-06-03 02:17:52.162000 | https://github.com/xpwu95/IP102 | 143 | Ip102: A large-scale benchmark dataset for insect pest recognition | https://scholar.google.com/scholar?cluster=4487446333535453318&hl=en&as_sdt=0,44 | 9 | 2,019 |
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment | 84 | cvpr | 14 | 0 | 2023-06-03 02:17:52.362000 | https://github.com/ParitoshParmar/MTL-AQA | 42 | What and how well you performed? a multitask learning approach to action quality assessment | https://scholar.google.com/scholar?cluster=16672989544412031563&hl=en&as_sdt=0,21 | 4 | 2,019 |
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation | 46 | cvpr | 9 | 1 | 2023-06-03 02:17:52.563000 | https://github.com/shuangjiexu/MHP-VOS | 62 | Mhp-vos: Multiple hypotheses propagation for video object segmentation | https://scholar.google.com/scholar?cluster=14226363239100634228&hl=en&as_sdt=0,33 | 6 | 2,019 |
SelFlow: Self-Supervised Learning of Optical Flow | 305 | cvpr | 63 | 6 | 2023-06-03 02:17:52.762000 | https://github.com/ppliuboy/SelFlow | 387 | Selflow: Self-supervised learning of optical flow | https://scholar.google.com/scholar?cluster=14077594709771456352&hl=en&as_sdt=0,21 | 14 | 2,019 |
UPSNet: A Unified Panoptic Segmentation Network | 367 | cvpr | 118 | 76 | 2023-06-03 02:17:52.962000 | https://github.com/uber-research/UPSNet | 625 | Upsnet: A unified panoptic segmentation network | https://scholar.google.com/scholar?cluster=18301475211197676940&hl=en&as_sdt=0,5 | 28 | 2,019 |
2.5D Visual Sound | 163 | cvpr | 17 | 2 | 2023-06-03 02:17:53.162000 | https://github.com/facebookresearch/FAIR-Play | 84 | 2.5 d visual sound | https://scholar.google.com/scholar?cluster=15955658488872503923&hl=en&as_sdt=0,33 | 9 | 2,019 |
Taking a Deeper Look at the Inverse Compositional Algorithm | 48 | cvpr | 29 | 2 | 2023-06-03 02:17:53.362000 | https://github.com/lvzhaoyang/DeeperInverseCompositionalAlgorithm | 152 | Taking a deeper look at the inverse compositional algorithm | https://scholar.google.com/scholar?cluster=16780531933965862286&hl=en&as_sdt=0,5 | 15 | 2,019 |
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds With Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields | 205 | cvpr | 34 | 2 | 2023-06-03 02:17:53.562000 | https://github.com/pqhieu/JSIS3D | 168 | Jsis3d: Joint semantic-instance segmentation of 3d point clouds with multi-task pointwise networks and multi-value conditional random fields | https://scholar.google.com/scholar?cluster=16927809821668290492&hl=en&as_sdt=0,5 | 7 | 2,019 |
Deeper and Wider Siamese Networks for Real-Time Visual Tracking | 820 | cvpr | 178 | 19 | 2023-06-03 02:17:53.761000 | https://github.com/researchmm/SiamDW | 737 | Deeper and wider siamese networks for real-time visual tracking | https://scholar.google.com/scholar?cluster=17696051770837517858&hl=en&as_sdt=0,33 | 24 | 2,019 |
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth | 248 | cvpr | 31 | 8 | 2023-06-03 02:17:53.961000 | https://github.com/davyneven/SpatialEmbeddings | 209 | Instance segmentation by jointly optimizing spatial embeddings and clustering bandwidth | https://scholar.google.com/scholar?cluster=14151595211459682440&hl=en&as_sdt=0,5 | 15 | 2,019 |
Parsing R-CNN for Instance-Level Human Analysis | 103 | cvpr | 36 | 25 | 2023-06-03 02:17:54.160000 | https://github.com/soeaver/Parsing-R-CNN | 283 | Parsing r-cnn for instance-level human analysis | https://scholar.google.com/scholar?cluster=5570486802749692020&hl=en&as_sdt=0,33 | 24 | 2,019 |
Semantic Correlation Promoted Shape-Variant Context for Segmentation | 164 | cvpr | 0 | 0 | 2023-06-03 02:17:54.360000 | https://github.com/henghuiding/SVC | 0 | Semantic correlation promoted shape-variant context for segmentation | https://scholar.google.com/scholar?cluster=16130229518023869149&hl=en&as_sdt=0,33 | 0 | 2,019 |
Perceive Where to Focus: Learning Visibility-Aware Part-Level Features for Partial Person Re-Identification | 311 | cvpr | 4 | 1 | 2023-06-03 02:17:54.561000 | https://github.com/YifanSun-ReID/VPM-reID | 28 | Perceive where to focus: Learning visibility-aware part-level features for partial person re-identification | https://scholar.google.com/scholar?cluster=4047481609137728387&hl=en&as_sdt=0,33 | 1 | 2,019 |
Relation-Shape Convolutional Neural Network for Point Cloud Analysis | 727 | cvpr | 74 | 20 | 2023-06-03 02:17:54.760000 | https://github.com/Yochengliu/Relation-Shape-CNN | 402 | Relation-shape convolutional neural network for point cloud analysis | https://scholar.google.com/scholar?cluster=11483419455001652603&hl=en&as_sdt=0,1 | 21 | 2,019 |
Meta-Transfer Learning for Few-Shot Learning | 976 | cvpr | 140 | 38 | 2023-06-03 02:17:54.960000 | https://github.com/yaoyao-liu/meta-transfer-learning | 661 | Meta-transfer learning for few-shot learning | https://scholar.google.com/scholar?cluster=16670100435832438519&hl=en&as_sdt=0,33 | 24 | 2,019 |
ATOM: Accurate Tracking by Overlap Maximization | 971 | cvpr | 577 | 55 | 2023-06-03 02:17:55.160000 | https://github.com/visionml/pytracking | 2,782 | Atom: Accurate tracking by overlap maximization | https://scholar.google.com/scholar?cluster=963225988420087018&hl=en&as_sdt=0,5 | 90 | 2,019 |
Visual Tracking via Adaptive Spatially-Regularized Correlation Filters | 366 | cvpr | 23 | 9 | 2023-06-03 02:17:55.361000 | https://github.com/Daikenan/ASRCF | 99 | Visual tracking via adaptive spatially-regularized correlation filters | https://scholar.google.com/scholar?cluster=1936083344177917118&hl=en&as_sdt=0,5 | 7 | 2,019 |
BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames | 40 | cvpr | 19 | 5 | 2023-06-03 02:17:55.560000 | https://github.com/griffbr/BubbleNets | 100 | Bubblenets: Learning to select the guidance frame in video object segmentation by deep sorting frames | https://scholar.google.com/scholar?cluster=1778787356825965594&hl=en&as_sdt=0,26 | 7 | 2,019 |
Deep RNN Framework for Visual Sequential Applications | 41 | cvpr | 13 | 0 | 2023-06-03 02:17:55.760000 | https://github.com/BoPang1996/Deep-RNN-Framework | 45 | Deep rnn framework for visual sequential applications | https://scholar.google.com/scholar?cluster=13952108559320750928&hl=en&as_sdt=0,1 | 6 | 2,019 |
Deep Tree Learning for Zero-Shot Face Anti-Spoofing | 207 | cvpr | 54 | 19 | 2023-06-03 02:17:55.961000 | https://github.com/yaojieliu/CVPR2019-DeepTreeLearningForZeroShotFaceAntispoofing | 180 | Deep tree learning for zero-shot face anti-spoofing | https://scholar.google.com/scholar?cluster=4809478454905690384&hl=en&as_sdt=0,32 | 13 | 2,019 |
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images | 104 | cvpr | 78 | 7 | 2023-06-03 02:17:56.161000 | https://github.com/chenwydj/ultra_high_resolution_segmentation | 312 | Collaborative global-local networks for memory-efficient segmentation of ultra-high resolution images | https://scholar.google.com/scholar?cluster=9353770986207663680&hl=en&as_sdt=0,25 | 12 | 2,019 |
Graph-Based Global Reasoning Networks | 416 | cvpr | 48 | 8 | 2023-06-03 02:17:56.361000 | https://github.com/facebookresearch/GloRe | 193 | Graph-based global reasoning networks | https://scholar.google.com/scholar?cluster=7036510083148234312&hl=en&as_sdt=0,5 | 9 | 2,019 |
ArcFace: Additive Angular Margin Loss for Deep Face Recognition | 4,654 | cvpr | 4,361 | 952 | 2023-06-03 02:17:56.561000 | https://github.com/deepinsight/insightface | 15,442 | Arcface: Additive angular margin loss for deep face recognition | https://scholar.google.com/scholar?cluster=14066082468781799933&hl=en&as_sdt=0,21 | 476 | 2,019 |
Efficient Parameter-Free Clustering Using First Neighbor Relations | 133 | cvpr | 53 | 0 | 2023-06-03 02:17:56.761000 | https://github.com/ssarfraz/FINCH-CLustering | 277 | Efficient parameter-free clustering using first neighbor relations | https://scholar.google.com/scholar?cluster=5006622334338007650&hl=en&as_sdt=0,5 | 22 | 2,019 |
Reversible GANs for Memory-Efficient Image-To-Image Translation | 41 | cvpr | 10 | 10 | 2023-06-03 02:17:56.962000 | https://github.com/tychovdo/RevGAN | 79 | Reversible gans for memory-efficient image-to-image translation | https://scholar.google.com/scholar?cluster=15019867665042081663&hl=en&as_sdt=0,33 | 10 | 2,019 |
Latent Space Autoregression for Novelty Detection | 386 | cvpr | 60 | 9 | 2023-06-03 02:17:57.162000 | https://github.com/aimagelab/novelty-detection | 185 | Latent space autoregression for novelty detection | https://scholar.google.com/scholar?cluster=18196632214960310707&hl=en&as_sdt=0,14 | 11 | 2,019 |
Feature Denoising for Improving Adversarial Robustness | 784 | cvpr | 86 | 2 | 2023-06-03 02:17:57.362000 | https://github.com/facebookresearch/ImageNet-Adversarial-Training | 664 | Feature denoising for improving adversarial robustness | https://scholar.google.com/scholar?cluster=961363392550158116&hl=en&as_sdt=0,39 | 20 | 2,019 |
Selective Kernel Networks | 1,592 | cvpr | 105 | 6 | 2023-06-03 02:17:57.562000 | https://github.com/implus/SKNet | 542 | Selective kernel networks | https://scholar.google.com/scholar?cluster=11785614849903023316&hl=en&as_sdt=0,5 | 9 | 2,019 |
FlowNet3D: Learning Scene Flow in 3D Point Clouds | 354 | cvpr | 84 | 18 | 2023-06-03 02:17:57.762000 | https://github.com/xingyul/flownet3d | 339 | Flownet3d: Learning scene flow in 3d point clouds | https://scholar.google.com/scholar?cluster=15188873080391320732&hl=en&as_sdt=0,47 | 13 | 2,019 |
Bag of Tricks for Image Classification with Convolutional Neural Networks | 1,246 | cvpr | 1,198 | 60 | 2023-06-03 02:17:57.961000 | https://github.com/dmlc/gluon-cv | 5,561 | Bag of tricks for image classification with convolutional neural networks | https://scholar.google.com/scholar?cluster=8341554460743296519&hl=en&as_sdt=0,33 | 154 | 2,019 |
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack | 228 | cvpr | 16 | 2 | 2023-06-03 02:17:58.163000 | https://github.com/elliothe/CVPR_2019_PNI | 38 | Parametric noise injection: Trainable randomness to improve deep neural network robustness against adversarial attack | https://scholar.google.com/scholar?cluster=3553606349914507364&hl=en&as_sdt=0,6 | 2 | 2,019 |
Strike (With) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects | 276 | cvpr | 16 | 0 | 2023-06-03 02:17:58.362000 | https://github.com/airalcorn2/strike-with-a-pose | 75 | Strike (with) a pose: Neural networks are easily fooled by strange poses of familiar objects | https://scholar.google.com/scholar?cluster=16755141960750698067&hl=en&as_sdt=0,11 | 5 | 2,019 |
SparseFool: A Few Pixels Make a Big Difference | 152 | cvpr | 11 | 0 | 2023-06-03 02:17:58.562000 | https://github.com/LTS4/SparseFool | 48 | Sparsefool: a few pixels make a big difference | https://scholar.google.com/scholar?cluster=6158227118856345030&hl=en&as_sdt=0,44 | 4 | 2,019 |
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-Identification | 572 | cvpr | 61 | 8 | 2023-06-03 02:17:58.762000 | https://github.com/zhunzhong07/ECN | 297 | Invariance matters: Exemplar memory for domain adaptive person re-identification | https://scholar.google.com/scholar?cluster=1740171451548448125&hl=en&as_sdt=0,5 | 11 | 2,019 |
Dissecting Person Re-Identification From the Viewpoint of Viewpoint | 180 | cvpr | 15 | 1 | 2023-06-03 02:17:58.971000 | https://github.com/sxzrt/Dissecting-Person-Re-ID-from-the-Viewpoint-of-Viewpoint | 117 | Dissecting person re-identification from the viewpoint of viewpoint | https://scholar.google.com/scholar?cluster=6413659946848887161&hl=en&as_sdt=0,1 | 8 | 2,019 |
Instance-Level Meta Normalization | 25 | cvpr | 3 | 0 | 2023-06-03 02:17:59.173000 | https://github.com/Gasoonjia/ILM-Norm | 17 | Instance-level meta normalization | https://scholar.google.com/scholar?cluster=17437121449575767985&hl=en&as_sdt=0,5 | 2 | 2,019 |
Iterative Normalization: Beyond Standardization Towards Efficient Whitening | 93 | cvpr | 4 | 0 | 2023-06-03 02:17:59.373000 | https://github.com/huangleiBuaa/IterNorm | 22 | Iterative normalization: Beyond standardization towards efficient whitening | https://scholar.google.com/scholar?cluster=17943009712133460569&hl=en&as_sdt=0,5 | 4 | 2,019 |
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells | 150 | cvpr | 25 | 2 | 2023-06-03 02:17:59.574000 | https://github.com/drsleep/nas-segm-pytorch | 143 | Fast neural architecture search of compact semantic segmentation models via auxiliary cells | https://scholar.google.com/scholar?cluster=8910584954060361446&hl=en&as_sdt=0,5 | 8 | 2,019 |
Generating 3D Adversarial Point Clouds | 214 | cvpr | 26 | 3 | 2023-06-03 02:17:59.774000 | https://github.com/xiangchong1/3d-adv-pc | 92 | Generating 3d adversarial point clouds | https://scholar.google.com/scholar?cluster=10039699469817980264&hl=en&as_sdt=0,5 | 6 | 2,019 |
Partial Order Pruning: For Best Speed/Accuracy Trade-Off in Neural Architecture Search | 128 | cvpr | 25 | 1 | 2023-06-03 02:17:59.974000 | https://github.com/lixincn2015/Partial-Order-Pruning | 147 | Partial order pruning: for best speed/accuracy trade-off in neural architecture search | https://scholar.google.com/scholar?cluster=8555049247914418659&hl=en&as_sdt=0,5 | 6 | 2,019 |
Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics | 204 | cvpr | 38 | 7 | 2023-06-03 02:18:00.175000 | https://github.com/Yunbo426/MIM | 137 | Memory in memory: A predictive neural network for learning higher-order non-stationarity from spatiotemporal dynamics | https://scholar.google.com/scholar?cluster=15070346920682817473&hl=en&as_sdt=0,5 | 5 | 2,019 |
Distilling Object Detectors With Fine-Grained Feature Imitation | 264 | cvpr | 70 | 22 | 2023-06-03 02:18:00.375000 | https://github.com/twangnh/Distilling-Object-Detectors | 402 | Distilling object detectors with fine-grained feature imitation | https://scholar.google.com/scholar?cluster=5085359464416711778&hl=en&as_sdt=0,11 | 10 | 2,019 |
Adapting Object Detectors via Selective Cross-Domain Alignment | 294 | cvpr | 15 | 4 | 2023-06-03 02:18:00.576000 | https://github.com/xinge008/SCDA | 78 | Adapting object detectors via selective cross-domain alignment | https://scholar.google.com/scholar?cluster=7497629776340245603&hl=en&as_sdt=0,20 | 2 | 2,019 |
Centripetal SGD for Pruning Very Deep Convolutional Networks With Complicated Structure | 162 | cvpr | 12 | 2 | 2023-06-03 02:18:00.775000 | https://github.com/ShawnDing1994/Centripetal-SGD | 59 | Centripetal sgd for pruning very deep convolutional networks with complicated structure | https://scholar.google.com/scholar?cluster=17050571465031021795&hl=en&as_sdt=0,5 | 5 | 2,019 |
Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation | 110 | cvpr | 5 | 2 | 2023-06-03 02:18:00.976000 | https://github.com/shenyunhang/WS-JDS | 19 | Cyclic guidance for weakly supervised joint detection and segmentation | https://scholar.google.com/scholar?cluster=764160567722431856&hl=en&as_sdt=0,5 | 1 | 2,019 |