Awesome-Causality-in-CV
A curated list of Causality in Computer Vision
https://github.com/Wangt-CN/Awesome-Causality-in-CV
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Table of Contents
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2021
- Transporting Causal Mechanisms for Unsupervised Domain Adaptation - zhongqi/tcm) |
- Causal Attention for Unbiased Visual Recognition - CN/CaaM) |
- Learning Causal Representation for Training Cross-Domain Pose Estimator via Generative Interventions - |
- Human Trajectory Prediction via Counterfactual Analysis
- Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-Identification
- The Blessings of Unlabeled Background in Untrimmed Videos - |
- Counterfactual VQA: A Cause-Effect Look at Language Bias
- Counterfactual Zero-Shot and Open-Set Visual Recognition - zhongqi/gcm-cf) |
- Distilling Causal Effect of Data in Class-Incremental Learning
- Causal Attention for Vision-Language Tasks
- Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality
- CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models - |
- Generative Interventions for Causal Learning - columbia/GenInt) |
- ACRE: Abstract Causal REasoning Beyond Covariation
- Towards Robust Classification Model by Counterfactual and Invariant Data Generation
- Interventional Video Grounding With Dual Contrastive Learning - |
- Representation Learning via Invariant Causal Mechanisms - |
- Counterfactual Generative Networks
- Distilling Causal Effect of Data in Class-Incremental Learning
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2020
- Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding - |
- A causal view of compositional zero-shot recognition - |
- Counterfactual Vision-and-Language Navigation: Unravelling the Unseen - |
- Causal Intervention for Weakly-Supervised Semantic Segmentation - NJUST/CONTA) |
- Interventional Few-Shot Learning - zhongqi/ifsl) |
- Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect - Tailed-Recognition.pytorch) |
- Towards causal benchmarking of bias in face analysis algorithms - eccv2020) |
- Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision - |
- Visual Commonsense R-CNN - CN/VC-R-CNN) |
- Unbiased scene graph generation from biased training - Graph-Benchmark.pytorch) |
- Two causal principles for improving visual dialog - principles) |
- Counterfactual samples synthesizing for robust visual question answering - VQA) |
- Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning - |
- Counterfactual Vision-and-Language Navigation via Adversarial Path Sampling - |
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Before 2020
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Arxiv
- Learning Causal Semantic Representation for Out-of-Distribution Prediction - |
- ECINN: Efficient Counterfactuals from Invertible Neural Networks - |
- A Structural Causal Model for MR Images of Multiple Sclerosis - |
- Counterfactual Variable Control for Robust and Interpretable Question Answering - QA) |
- Deconfounded Image Captioning: A Causal Retrospect - |
- Latent Causal Invariant Model - |
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