3 citations · 4 across the 10 of their papers we have counts for
12 papers
ECHO: Event-Augmented Context with Hindsight and Outlook for Wrist-Only Manipulation
Xinyue Wang, Yicheng Jiang, Zesen Gan +8
Learning-based manipulation policies relying on RGB cameras often suffer from degraded observations under extreme exposure. Event cameras mitigate this degradation by asynchronousl…
AR-WAM: A Visual-Conditioned Agent-Ready World Action Model for Robotic Manipulation
Yicheng Jiang, Zesen Gan, Xiaobo Wang +8
As AI agents become increasingly capable, agent-driven robotic control is emerging as a compelling paradigm. However, prevailing vision-language-action (VLA) models and world actio…
OSOR: One-Step Diffusion Inpainting for Effect-Aware Object Removal
Qinming Zhou, Chenxi Sun, Deyang Kong +6
Real-world object removal is challenging due to two key difficulties: the target object's non-local effects, such as shadows and reflections, which are difficult to model, and the…
MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual Anisotropy
Jiaxu Wang, Junhao He, Jingkai Sun +5
Learning real-world dynamics from visual observations is crucial for various domains. A common strategy is to calibrate simulators by estimating physical parameters, yet accuracy i…
Learning Structural Latent Points for Efficient Visual Representations in Robotic Manipulation
Yicheng Jiang, Jiaxu Wang, Junhao He +8
Current 3D-aware pretraining methods for embodied perception and manipulation are largely built on differentiable rendering frameworks, producing either fully implicit neural field…
MVISTA-4D: View-Consistent 4D World Model with Test-Time Action Inference for Robotic Manipulation
Jiaxu Wang, Yicheng Jiang, Tianlun He +8
World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely image-based forecasting or reasoni…
DEGS: Deformable Event-based 3D Gaussian Splatting from RGB and Event Stream
Junhao He, Jiaxu Wang, Jia Li +7
Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the sol…
DEL: Discrete Element Learner for Learning 3D Particle Dynamics with Neural Rendering
Jiaxu Wang, Jingkai Sun, Junhao He +4
Learning-based simulators show great potential for simulating particle dynamics when 3D groundtruth is available, but per-particle correspondences are not always accessible. The de…
PFGS: High Fidelity Point Cloud Rendering via Feature Splatting
Jiaxu Wang, Ziyi Zhang, Junhao He +1
Rendering high-fidelity images from sparse point clouds is still challenging. Existing learning-based approaches suffer from either hole artifacts, missing details, or expensive co…
Query-based Semantic Gaussian Field for Scene Representation in Reinforcement Learning
Jiaxu Wang, Ziyi Zhang, Qiang Zhang +5
Latent scene representation plays a significant role in training reinforcement learning (RL) agents. To obtain good latent vectors describing the scenes, recent works incorporate t…
EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting
Jiaxu Wang, Junhao He, Ziyi Zhang +3
Event cameras offer promising advantages such as high dynamic range and low latency, making them well-suited for challenging lighting conditions and fast-moving scenarios. However,…
Physical Priors Augmented Event-Based 3D Reconstruction
Jiaxu Wang, Junhao He, Ziyi Zhang +1
3D neural implicit representations play a significant component in many robotic applications. However, reconstructing neural radiance fields (NeRF) from realistic event data remain…