| 일 | 월 | 화 | 수 | 목 | 금 | 토 |
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||
| 5 | 6 | 7 | 8 | 9 | 10 | 11 |
| 12 | 13 | 14 | 15 | 16 | 17 | 18 |
| 19 | 20 | 21 | 22 | 23 | 24 | 25 |
| 26 | 27 | 28 | 29 | 30 | 31 |
- Multi-modal
- Prompt Tuning
- active learning
- Data-centric AI
- Prompt란
- iclr spotlight
- deep learning
- Segment Anything 리뷰
- ICLR
- ai 최신 논문
- Segment Anything 설명
- cvpr 논문 리뷰
- ssl
- Stable Diffusion
- 자기지도학습
- 논문리뷰
- 논문 리뷰
- iclr 논문 리뷰
- Computer Vision
- Data-centric
- CVPR
- Computer Vision 논문 리뷰
- Segment Anything
- Self-supervised learning
- contrastive learning
- deep learning 논문 리뷰
- VLM
- Meta AI
- iclr 2024
- cvpr 2024
- Today
- Total
목록Segment Anything 설명 (2)
Study With Inha
[Paper Review] 고해상도 결과를 얻을 수 있는 Segment Anything 후속 연구, HQ-SAM 논문 리뷰
Segment Anything in High Quality, ETH Zurich 논문링크: https://arxiv.org/abs/2306.01567 Segment Anything in High QualityThe recent Segment Anything Model (SAM) represents a big leap in scaling up segmentation models, allowing for powerful zero-shot capabilities and flexible prompting. Despite being trained with 1.1 billion masks, SAM's mask prediction quality falls short inarxiv.org Introduction올해 상..
[Paper Review] Segment Anything Model (SAM) 자세한 논문 리뷰, Meta의 Segment Anything 설명
Meta AI, Segment Anything, Alexander Kirillov et al.논문 링크: https://ai.facebook.com/research/publications/segment-anything/ (SAM 후속 논문 리뷰 링크) Meta AI, SAM 2: Segment Anything in Images and Videos 논문 리뷰 및 SAM2 설명 [Paper Review] Meta AI, SAM 2: Segment Anything in Images and Videos 논문 리뷰 및 SAM2 설명Meta FAIR SAM 2: Segment Anything in Images and Videos SAM2 설명 및 논문 리뷰Paper: SAM2 Paper LinkDemo: https..