| {"paper_url": "https://arxiv.org/abs/2112.10003", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation](https://huggingface.co/papers/2406.05271) (2024)\n* [Enhancing Vision-Language Model with Unmasked Token Alignment](https://huggingface.co/papers/2405.19009) (2024)\n* [Unsupervised Pre-training with Language-Vision Prompts for Low-Data Instance Segmentation](https://huggingface.co/papers/2405.13388) (2024)\n* [Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation](https://huggingface.co/papers/2406.00670) (2024)\n* [Zero Shot Context-Based Object Segmentation using SLIP (SAM+CLIP)](https://huggingface.co/papers/2405.07284) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"} |