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- Class Incremental
- img2pose: Face Alignment and Detection via 6DoF
- Discrete diffusion
- Vector Quantized Diffusion Model for Text-to-Image Synthesis
- VQ-VAE
- CIL
- ENERGY-BASED MODELS FOR CONTINUAL LEARNING
- timm
- CVPR2022
- Markov transition matrix
- Class Incremental Learning
- Face Alignment
- mmcv
- Mask-and-replace diffusion strategy
- requires_grad
- Continual Learning
- Img2pose
- learning to prompt for continual learning
- DualPrompt
- learning to prompt
- state_dict()
- Face Pose Estimation
- Facial Landmark Localization
- Mask diffusion
- VQ-diffusion
- Energy-based model
- L2P
- prompt learning
- PnP algorithm
- 베이지안 정리
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목록prompt learning (2)
Computer Vision , AI
[One-page summary] DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning (ECCV 2022) By Wang et al.
●Summary: Learning two disjoint prompt spaces makes rehearsal-free prompt-based continual learning more effectively ●Approach highlight ○Using task-invariant General prompt(L_g) at ViT 1~2nd layer and task-specific Expert Prompt(# of task ×L_e) at ViT 3~5th layer ○Prefix tuning: before MSA, concatenate key prompt to hidden representation of key and value prompt to hidden representation of value,..
[One-page summary] Learning to Prompt for Continual Learning (CVPR 2022) By Wang et al.
Category: continual learning (class incremental) ●Summary: Use prompt with a pre-trained model for rehearsal buffer-free and task-agnostic continual learning ●Approach highlight ○Prompt pool memory space allows rehearsal buffer-free and task-agnostic ○ Penalize frequently-used prompts by using prompt frequency table H_t at training time for the diversity of prompt (1) ○ At training-time, If quer..