Research map / Reinforcement learning / Visual and representation RL
Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace PadCrop with Random PadResize as DA | DrQ-V2 · DMC 12-task average | average episode return: 547.96 -> 588.75 | Helped |
| replace PadCrop with Random PadResize as DA | DrQ-V2 · CARLA 200k average | average episode return: 217.8 -> 227.7 | Helped |
| add CycAug cycling between PadCrop and Rand PR | DrQ-V2 · DMC 12-task average | average episode return: 547.96 -> 654.83 | Helped |
| add CycAug cycling between PadCrop and Rand PR | DrQ-V2 · CARLA 100k average | average episode return: 99.7 -> 143.3 | Helped |
| add CycAug cycling between PadCrop and Rand PR | DrQ-V2 · CARLA 200k average | average episode return: 217.8 -> 269.7 | Helped |
| increase DA hardness (ablation) | individual DA operations on DrQ-V2 · DMC tasks | IQM return | Hurt |
| increase spatial diversity of DA (ablation) | individual DA operations on DrQ-V2 · DMC tasks | IQM return | Helped |
| increase strength diversity of DA (ablation) | individual DA operations on DrQ-V2 · DMC tasks | IQM return | Mixed |
| use composing/sampling/mixing fusion of two DA types instead of an individual operation (ablation) | DrQ-V2 · DMC Quadruped Run | episode return | Hurt |
| add a third DA (CS) to CycAug PC+PR (ablation) | CycAug · DMC | sample efficiency | Helped |
Closest papers by meaning
- Revisiting Data Augmentation in Deep Reinforcement Learning (ICLR 2024 · similarity 0.91)
- Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates (ICLR 2024 · similarity 0.90)
- The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning (NeurIPS 2024 · similarity 0.87)
- Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages (ICLR 2024 · similarity 0.87)
- VIGOR: Zero-Shot Visual Generalization via Latent-Space Consistency in Model-Based Reinforcement Learning (NeurIPS 2026 · similarity 0.87)
- Zero Shot Generalization of Vision-Based RL Without Data Augmentation (ICML 2025 · similarity 0.87)
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