Article
Open-source DeepResearch – Freeing our search agents
•
1.07k
tevy kuch
tevykuch
AI & ML interests
None yet
Recent Activity
upvoted
an
article
17 days ago
Open-source DeepResearch – Freeing our search agents
upvoted
a
paper
23 days ago
Agent Laboratory: Using LLM Agents as Research Assistants
liked
a model
10 months ago
SG161222/Realistic_Vision_V6.0_B1_noVAE
Organizations
tevykuch's activity
upvoted
an
article
17 days ago
upvoted
a
paper
23 days ago
liked
a
model
10 months ago
upvoted
an
article
10 months ago
Article
How to generate text: using different decoding methods for language generation with Transformers
•
157
liked
a
dataset
10 months ago
liked
a
model
10 months ago
liked
a
Space
10 months ago
updated
a
Space
12 months ago
reacted to
DmitryRyumin's
post with ❤️
12 months ago
Post
🚀🖼️🌟 New Research Alert - CVPR 2024! 🌟🖼️🚀
📄 Title: CAMixerSR: Only Details Need More "Attention" 🌟🚀
📝 Description: CAMixerSR is a new approach integrating content-aware accelerating framework and token mixer design, to pursue more efficient SR inference via assigning convolution for simple regions but window-attention for complex textures. It exhibits excellent generality and attains competitive results among state-of-the-art models with better complexity-performance trade-offs on large-image SR, lightweight SR, and omnidirectional-image SR.
👥 Authors: Yan Wang, Shijie Zhao, Yi Liu, Junlin Li, and Li Zhang
📅 Conference: CVPR, Jun 17-21, 2024 | Seattle WA, USA 🇺🇸
🔗 Paper: CAMixerSR: Only Details Need More "Attention" (2402.19289)
🔗 Repository: https://github.com/icandle/CAMixerSR
📚 More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
🚀 Added to the Image Enhancement Collection: DmitryRyumin/image-enhancement-65ee1cd2fe1c0c877ae55d28
🔍 Keywords: #CAMixerSR #SuperResolution #WindowAttention #ImageEnhancement #CVPR2024 #DeepLearning #Innovation
📄 Title: CAMixerSR: Only Details Need More "Attention" 🌟🚀
📝 Description: CAMixerSR is a new approach integrating content-aware accelerating framework and token mixer design, to pursue more efficient SR inference via assigning convolution for simple regions but window-attention for complex textures. It exhibits excellent generality and attains competitive results among state-of-the-art models with better complexity-performance trade-offs on large-image SR, lightweight SR, and omnidirectional-image SR.
👥 Authors: Yan Wang, Shijie Zhao, Yi Liu, Junlin Li, and Li Zhang
📅 Conference: CVPR, Jun 17-21, 2024 | Seattle WA, USA 🇺🇸
🔗 Paper: CAMixerSR: Only Details Need More "Attention" (2402.19289)
🔗 Repository: https://github.com/icandle/CAMixerSR
📚 More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin
🚀 Added to the Image Enhancement Collection: DmitryRyumin/image-enhancement-65ee1cd2fe1c0c877ae55d28
🔍 Keywords: #CAMixerSR #SuperResolution #WindowAttention #ImageEnhancement #CVPR2024 #DeepLearning #Innovation
updated
a
model
12 months ago
updated
a
Space
12 months ago
updated
2
models
12 months ago
upvoted
a
paper
about 1 year ago
updated
a
model
over 1 year ago