110 citations · 387 across the 42 of their papers we have counts for
15 papers · 1 filter
HumanNeRF: Efficiently Generated Human Radiance Field from Sparse Inputs
Fuqiang Zhao, Wei Yang, Jiakai Zhang +4
Recent neural human representations can produce high-quality multi-view rendering but require using dense multi-view inputs and costly training. They are hence largely limited to s…
Towards Controllable and Photorealistic Region-wise Image Manipulation
Ansheng You, Chenglin Zhou, Qixuan Zhang +1
Adaptive and flexible image editing is a desirable function of modern generative models. In this work, we present a generative model with auto-encoder architecture for per-region s…
iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Rendering
Liao Wang, Ziyu Wang, Pei Lin +5
Generating ``bullet-time'' effects of human free-viewpoint videos is critical for immersive visual effects and VR/AR experience. Recent neural advances still lack the controllable…
Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions
Guoxing Sun, Xin Chen, Yizhang Chen +6
4D reconstruction of human-object interaction is critical for immersive VR/AR experience and human activity understanding. Recent advances still fail to recover fine geometry and t…
Neural Relighting and Expression Transfer On Video Portraits
Youjia Wang, Taotao Zhou, Minzhang Li +4
Photo-realistic video portrait reenactment benefits virtual production and numerous VR/AR experiences. The task remains challenging as the reenacted expression should match the sou…
Few-shot Neural Human Performance Rendering from Sparse RGBD Videos
Anqi Pang, Xin Chen, Haimin Luo +3
Recent neural rendering approaches for human activities achieve remarkable view synthesis results, but still rely on dense input views or dense training with all the capture frames…
IREM: High-Resolution Magnetic Resonance (MR) Image Reconstruction via Implicit Neural Representation
Qing Wu, Yuwei Li, Lan Xu +7
For collecting high-quality high-resolution (HR) MR image, we propose a novel image reconstruction network named IREM, which is trained on multiple low-resolution (LR) MR images an…
PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging
Yuwei Li, Minye Wu, Yuyao Zhang +2
Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare. Existing parametric models account only for hand shape, pose, or texture, without modeling…
MirrorNeRF: One-shot Neural Portrait Radiance Field from Multi-mirror Catadioptric Imaging
Ziyu Wang, Liao Wang, Fuqiang Zhao +3
Photo-realistic neural reconstruction and rendering of the human portrait are critical for numerous VR/AR applications. Still, existing solutions inherently rely on multi-view capt…
Editable Free-viewpoint Video Using a Layered Neural Representation
Jiakai Zhang, Xinhang Liu, Xinyi Ye +6
Generating free-viewpoint videos is critical for immersive VR/AR experience but recent neural advances still lack the editing ability to manipulate the visual perception for large…
Convolutional Neural Opacity Radiance Fields
Haimin Luo, Anpei Chen, Qixuan Zhang +4
Photo-realistic modeling and rendering of fuzzy objects with complex opacity are critical for numerous immersive VR/AR applications, but it suffers from strong view-dependent brigh…
SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos
Xin Chen, Anqi Pang, Wei Yang +3
Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-…
Neural Video Portrait Relighting in Real-time via Consistency Modeling
Longwen Zhang, Qixuan Zhang, Minye Wu +2
Video portraits relighting is critical in user-facing human photography, especially for immersive VR/AR experience. Recent advances still fail to recover consistent relit result un…
ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal References
Yannan He, Anqi Pang, Xin Chen +4
Capturing challenging human motions is critical for numerous applications, but it suffers from complex motion patterns and severe self-occlusion under the monocular setting. In thi…
GNeRF: GAN-based Neural Radiance Field without Posed Camera
Quan Meng, Anpei Chen, Haimin Luo +5
We introduce GNeRF, a framework to marry Generative Adversarial Networks (GAN) with Neural Radiance Field (NeRF) reconstruction for the complex scenarios with unknown and even rand…