Learning Better with Less: Effective Augmentation for Sample-Efficient
Visual Reinforcement Learning

Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning

25 May 2023

Li Shen

Papers citing "Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning"

8 / 8 papers shown

Title
Sliding Puzzles Gym: A Scalable Benchmark for State Representation in Visual Reinforcement Learning Bryan L. M. de Oliveira Murilo L. da Luz Bruno Brandão Luana G. B. Martins Telma W. de L. Soares L. Melo OffRL 60 1 0 17 Feb 2025
Intrinsic Dynamics-Driven Generalizable Scene Representations for Vision-Oriented Decision-Making Applications Dayang Liang Jinyang Lai Yunlong Liu 26 0 0 30 May 2024
Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification Puru Vaish Shunxin Wang N. Strisciuglio 27 8 0 04 Mar 2024
Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages Guozheng Ma Lu Li Sen Zhang Zixuan Liu Zhen Wang Yixin Chen Li Shen Xueqian Wang Dacheng Tao OffRL 40 14 0 11 Oct 2023
Normalization Enhances Generalization in Visual Reinforcement Learning Lu Li Jiafei Lyu Guozheng Ma Zilin Wang Zhen Yang Xiu Li Zhiheng Li OOD 17 8 0 01 Jun 2023
Masked World Models for Visual Control Younggyo Seo Danijar Hafner Hao Liu Fangchen Liu Stephen James Kimin Lee Pieter Abbeel OffRL 77 144 0 28 Jun 2022
The Primacy Bias in Deep Reinforcement Learning Evgenii Nikishin Max Schwarzer P. DÓro Pierre-Luc Bacon Aaron C. Courville OnRL 85 178 0 16 May 2022
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi Yin Cui A. Srinivas Rui Qian Tsung-Yi Lin E. D. Cubuk Quoc V. Le Barret Zoph ISeg 223 962 0 13 Dec 2020