3 citations · 6 across the 10 of their papers we have counts for
11 papers
HandFlow: Fully Generative 4D Hand Recovery with Flow Matching
Mingxi Xu, Bowen Duan, Yi Gu +3
Accurate monocular 4D hand reconstruction remains challenging. Per-frame discriminative regressors lack temporal context and often produce jittery predictions. Temporal models impr…
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…
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…
FixingGS: Enhancing 3D Gaussian Splatting via Training-Free Score Distillation
Zhaorui Wang, Yi Gu, Deming Zhou +1
Recently, 3D Gaussian Splatting (3DGS) has demonstrated remarkable success in 3D reconstruction and novel view synthesis. However, reconstructing 3D scenes from sparse viewpoints r…
Learning Null Geodesics for Gravitational Lensing Rendering in General Relativity
Mingyuan Sun, Zheng Fang, Jiaxu Wang +3
We present GravLensX, an innovative method for rendering black holes with gravitational lensing effects using neural networks. The methodology involves training neural networks to…
Robust SG-NeRF: Robust Scene Graph Aided Neural Surface Reconstruction
Yi Gu, Dongjun Ye, Zhaorui Wang +3
Neural surface reconstruction relies heavily on accurate camera poses as input. Despite utilizing advanced pose estimators like COLMAP or ARKit, camera poses can still be noisy. Ex…
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…
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,…
EventRPG: Event Data Augmentation with Relevance Propagation Guidance
Mingyuan Sun, Donghao Zhang, Zongyuan Ge +4
Event camera, a novel bio-inspired vision sensor, has drawn a lot of attention for its low latency, low power consumption, and high dynamic range. Currently, overfitting remains a…
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…
Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation
Jiaxu Wang, Ziyi Zhang, Renjing Xu
This paper introduces a novel paradigm for the generalizable neural radiance field (NeRF). Previous generic NeRF methods combine multiview stereo techniques with image-based neural…