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Self-Supervised Visual On-Policy Distillation

158 upvotes · 14 AUG 2026 · Yijiang Li, Yijun Liang, Yunjie Tian et al.

This paper proposes a new method called Self-Supervised Visual On-Policy Distillation (S^2VOPD) that generates learning signals from asymmetric augmented views of images, allowing for effective on-policy learning without privileged information. Practitioners might care about this paper because it presents a simple yet effective way to improve performance on various perception benchmarks.

visual augmentationon-policy learningself-supervised learningdistillationreinforcement learning