BetaRare
hila-chefer/Transformer-MM-Explainability
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
- Owner
- hila-chefer (personal account)
- Stars
- Stars: 914
- Forks
- Forks: 118
- Language
- Jupyter Notebook
- License
- MIT
- Created
- 2021
- Topics
- transformerstransformervqadetrvisualizationexplainabilityexplainable-aiinterpretabilitylxmertvisualbert
- Tier
- Beta (700 to 1,999 ★) What this tier means
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