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20232026
most citedWorld-Grounded Human Motion Recovery via Gravity-View Coordinates

33 citations · 43 across the 15 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.AI2026

Scaling Discovery Requires Forgetting

Shangyin Tan, Ben Zhou, Lakshya A Agrawal +8

Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are capable of discovering new idea…

cs.CV2026

InfiniSplat: Implicit Gaussian Decoding for Large-Baseline Monocular View Synthesis

Jiawei Wang, Hao Yu, Yongzhen Hu +7

Single-image feed-forward 3D Gaussian Splatting (3DGS) aims to directly generate a renderable 3D scene representation from one input image, avoiding the cost of multi-view capture…

cs.RO2026

AutoPath: Learning Transferable Goal-Conditioned Stochastic Path Prior for Safe Navigation Without Human Demonstrations

Ziyang Zhang, Boyang Zhou, Zesong Yang +8

Real-time navigation in cluttered and dynamic environments requires collision-free and dynamically feasible motion under limited perception. However, feasible navigation behaviors…

cs.RO2026

Habitat-GS: A High-Fidelity Navigation Simulator with Dynamic Gaussian Splatting

Ziyuan Xia, Jingyi Xu, Chong Cui +9

Training embodied AI agents depends critically on the visual fidelity of simulation environments and the ability to model dynamic humans. Current simulators predominantly rely on m…

cs.GR2026

PhysSkin: Real-Time and Generalizable Physics-Based Animation via Self-Supervised Neural Skinning

Yuanhang Lei, Tao Cheng, Xingxuan Li +6

Achieving real-time physics-based animation that generalizes across diverse 3D shapes and discretizations remains a fundamental challenge. We introduce PhysSkin, a physics-informed…

cs.CV2026

DiffWind: Physics-Informed Differentiable Modeling of Wind-Driven Object Dynamics

Yuanhang Lei, Boming Zhao, Zesong Yang +10

Modeling wind-driven object dynamics from video observations is highly challenging due to the invisibility and spatio-temporal variability of wind, as well as the complex deformati…

cs.CV2026

InfiniDepth: Arbitrary-Resolution and Fine-Grained Depth Estimation with Neural Implicit Fields

Hao Yu, Haotong Lin, Jiawei Wang +7

Existing depth estimation methods are fundamentally limited to predicting depth on discrete image grids. Such representations restrict their scalability to arbitrary output resolut…