1 citations · 2 across the 5 of their papers we have counts for
8 papers
Policy Plasticity Matters in Offline-to-Online Reinforcement Learning: Refitting Offline Policies for Online Adaptation
Yuheng Huang, Yunpeng Qing, Yixiao Chi +2
Offline-to-Online Reinforcement Learning (O2O RL) has emerged as a practical paradigm that pre-trains the policy using static offline datasets and subsequently adapts the policy th…
PF-RL: Progress Field Reinforcement Learning via Goal-Conditioned Value Geometry for Vision-Language-Action Models
Yunpeng Qing, Yilun Kong, Sixu Lin +9
Reinforcement Fine-Tuning~(RFT) has emerged as a promising paradigm for improving Vision-Language-Action~(VLA) policies, yet sparse task-level outcomes provide limited credit for i…
PhysRVG: Physics-Aware Unified Reinforcement Learning for Video Generative Models
Qiyuan Zhang, Biao Gong, Shuai Tan +7
Physical principles are fundamental to realistic visual simulation, but remain a significant oversight in transformer-based video generation. This gap highlights a critical limitat…
BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning
Yunpeng Qing, Yixiao Chi, Shuo Chen +5
Recent advances in offline Reinforcement Learning (RL) have proven that effective policy learning can benefit from imposing conservative constraints on pre-collected datasets. Howe…
DecoupledGaussian: Object-Scene Decoupling for Physics-Based Interaction
Miaowei Wang, Yibo Zhang, Rui Ma +3
We present DecoupledGaussian, a novel system that decouples static objects from their contacted surfaces captured in-the-wild videos, a key prerequisite for realistic Newtonian-bas…
Diff3DS: Generating View-Consistent 3D Sketch via Differentiable Curve Rendering
Yibo Zhang, Lihong Wang, Changqing Zou +2
3D sketches are widely used for visually representing the 3D shape and structure of objects or scenes. However, the creation of 3D sketch often requires users to possess profession…
Manifold Path Guiding for Importance Sampling Specular Chains
Zhimin Fan, Pengpei Hong, Jie Guo +3
Complex visual effects such as caustics are often produced by light paths containing multiple consecutive specular vertices (dubbed specular chains), which pose a challenge to unbi…
PointNorm-Net: Self-Supervised Normal Prediction of 3D Point Clouds via Multi-Modal Distribution Estimation
Jie Zhang, Minghui Nie, Changqing Zou +3
Although supervised deep normal estimators have recently shown impressive results on synthetic benchmarks, their performance deteriorates significantly in real-world scenarios due…