Notice
Recent Posts
Recent Comments
Link
| ์ผ | ์ | ํ | ์ | ๋ชฉ | ๊ธ | ํ |
|---|---|---|---|---|---|---|
| 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 |
Tags
- requires_grad
- Facial Landmark Localization
- Img2pose
- Mask-and-replace diffusion strategy
- Mask diffusion
- Class Incremental
- CIL
- Markov transition matrix
- learning to prompt for continual learning
- Energy-based model
- Face Alignment
- VQ-VAE
- state_dict()
- Discrete diffusion
- CVPR2022
- PnP algorithm
- Continual Learning
- ENERGY-BASED MODELS FOR CONTINUAL LEARNING
- DualPrompt
- learning to prompt
- Vector Quantized Diffusion Model for Text-to-Image Synthesis
- mmcv
- timm
- Face Pose Estimation
- ๋ฒ ์ด์ง์ ์ ๋ฆฌ
- VQ-diffusion
- prompt learning
- L2P
- img2pose: Face Alignment and Detection via 6DoF
- Class Incremental Learning
Archives
- Today
- Total
Computer Vision , AI
[One-page summary] A Light Touch Approach to Teaching Transformers Multi-view Geometry(CVPR 2023) by Zisserman et al. ๋ณธ๋ฌธ
Paper_review[short]
[One-page summary] A Light Touch Approach to Teaching Transformers Multi-view Geometry(CVPR 2023) by Zisserman et al.
Elune001 2024. 1. 15. 21:37โ Summary: Multi-view geometry improves object retrieval performance
โApproach highlight
- Reranking transformer for object retrieval
-
Epipolar Loss and Max-Epipolar Loss: Using epiploar line to utilize multi-view image
$๐ด^{12}, ๐ด^{21}$: cross attention map from last transformer ๐(๐,๐): indicator function. if (๐,๐)on epipolar line then 1, else 0
โ Main Results
โ Discussion
- No significant performance improvements (what is the drawback? Is it a really good idea to use the Epiploar geometry view?)
'Paper_review[short]' ์นดํ ๊ณ ๋ฆฌ์ ๋ค๋ฅธ ๊ธ
'Paper_review[short]' Related Articles
more
