activity
20192026
most citedNon-Rigid Point Set Registration Networks

34 citations · 38 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

EgoRelight: Egocentric Human Capture and Illumination Recovery for Relightable and Photoreal Avatar Rendering

Jianchun Chen, Yinda Zhang, Rohit Pandey +3

Mixed Reality (MR) headsets promise a future of immersive telepresence where virtual humans blend indistinguishably into real or virtual surroundings. Achieving this vision require…

cs.CV2026

Faster 3D Gaussian Splatting Convergence via Structure-Aware Densification

Linjie Lyu, Ayush Tewari, Jianchun Chen +2

3D Gaussian Splatting has emerged as a powerful scene representation for real-time novel-view synthesis. However, its standard adaptive density control relies on screen-space posit…

cs.CV2025

OLATverse: A Large-scale Real-world Object Dataset with Precise Lighting Control

Xilong Zhou, Jianchun Chen, Pramod Rao +7

We introduce OLATverse, a large-scale dataset comprising around 9M images of 765 real-world objects, captured from multiple viewpoints under a diverse set of precisely controlled l…

cs.CV2025

Relightable Holoported Characters: Capturing and Relighting Dynamic Human Performance from Sparse Views

Kunwar Maheep Singh, Jianchun Chen, Vladislav Golyanik +5

We present Relightable Holoported Characters (RHC), a novel person-specific method for free-view rendering and relighting of full-body and highly dynamic humans solely observed fro…

cs.CV2024

EgoAvatar: Egocentric View-Driven and Photorealistic Full-body Avatars

Jianchun Chen, Jian Wang, Yinda Zhang +4

Immersive VR telepresence ideally means being able to interact and communicate with digital avatars that are indistinguishable from and precisely reflect the behaviour of their rea…

cs.CV20204 cited

Robust Image Matching By Dynamic Feature Selection

Hao Huang, Jianchun Chen, Xiang Li +2

Estimating dense correspondences between images is a long-standing image under-standing task. Recent works introduce convolutional neural networks (CNNs) to extract high-level feat…