Research map / Label-efficient and robust learning / Domain adaptation and generalization
Gotta Adapt 'Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace DANN with DANN-CA | Feature-level adaptation · CompCars surveillance test | accuracy: 60.40 -> 75.83 | Helped |
| Replace CycleGAN with AC-CGAN (ablation) | Photometric pixel adaptation · CompCars surveillance test | accuracy: 64.32 -> 67.30 | Helped |
| Add MKF perspective transformation (ablation) | CycleGAN photometric adaptation · CompCars surveillance test | accuracy: 64.32 -> 71.21 | Helped |
| Add AC-CGAN instead of CycleGAN (ablation) | MKF pixel adaptation · CompCars surveillance test | accuracy: 71.21 -> 79.71 | Helped |
| Add MKF and AC-CGAN (ablation) | DANN-CA · CompCars surveillance test | accuracy: 75.83 -> 84.20 | Helped |
| Use keypoint-based AF instead of image-input AF (ablation) | Perspective transformation · CompCars surveillance test | accuracy: 59.73 -> 61.55 | Helped |
| Add a mask to KF (ablation) | Perspective transformation · CompCars surveillance test | accuracy: 61.55 -> 64.30 | Helped |
| Replace DANN with DANN-CA | Feature-level adaptation · SVHN→MNIST | accuracy: 88.70 -> 96.23 | Helped |
| Replace DANN with DANN-CA | Feature-level adaptation · Office-31 A→W | accuracy: 85.97 -> 91.35 | Helped |
| Use a single AC-CGAN generator rather than separate day and night generators (ablation) | AC-CGAN · CompCars surveillance test | accuracy | Hurt |
| Remove perspective transformation (ablation) | CycleGAN pixel adaptation · CompCars surveillance test | accuracy: 71.21 -> 64.32 | Hurt |
Closest papers by meaning
- Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection (CVPR 2019 · similarity 0.88)
- A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018 · similarity 0.87)
- Approximate Domain Unlearning for Vision-Language Models (NeurIPS 2025 · similarity 0.87)
- LEARNING FACTORIZED REPRESENTATIONS FOR OPEN-SET DOMAIN ADAPTATION (ICLR 2019 · similarity 0.87)
- Domain-Specific Suppression for Adaptive Object Detection (CVPR 2021 · similarity 0.87)
- Adversarial Discriminative Domain Adaptation (CVPR 2017 · similarity 0.86)
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