CiV21
* *Causality in Vision
* DeVLBert: Out-of-distribution Visio-Linguistic Pretraining with Causality
* Grounded, Controllable and Debiased Image Completion with Lexical Semantics
* Instance-wise Causal Feature Selection for Model Interpretation
* Learning Contextual Causality between Daily Events from Time-consecutive Images
* Shadow-Mapping for Unsupervised Neural Causal Discovery
CiV22
* *Causality in Vision
* Bag of Tricks for Out-of-distribution Generalization
* Bootstrap Generalization Ability from Loss Landscape Perspective
* Decoupled Mixup for Out-of-distribution Visual Recognition
* Deep Structural Causal Shape Models
* Domain Generalization with Global Sample Mixup
* Investigating Neural Network Training on a Feature Level Using Conditional Independence
* Meta-causal Feature Learning for Out-of-distribution Generalization
* Nico Challenge: Out-of-distribution Generalization for Image Recognition Challenges
* Simpledg: Simple Domain Generalization Baseline Without Bells and Whistles
* Three-stage Model Fusion Method for Out-of-distribution Generalization, A
* Towards Interpreting Computer Vision Based on Transformation Invariant Optimization
12 for CiV22