20 citations · 45 across the 13 of their papers we have counts for
13 papers
Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis
Zhan Li, Zhang Chen, Zhong Li +1
Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem. Despite recent advancements, simultaneously achieving high-resolution photorealistic results,…
Relit-NeuLF: Efficient Relighting and Novel View Synthesis via Neural 4D Light Field
Zhong Li, Liangchen Song, Zhang Chen +4
In this paper, we address the problem of simultaneous relighting and novel view synthesis of a complex scene from multi-view images with a limited number of light sources. We propo…
NeuRBF: A Neural Fields Representation with Adaptive Radial Basis Functions
Zhang Chen, Zhong Li, Liangchen Song +4
We present a novel type of neural fields that uses general radial bases for signal representation. State-of-the-art neural fields typically rely on grid-based representations for s…
High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition
Tianyu Luan, Yuanhao Zhai, Jingjing Meng +4
Despite the impressive performance obtained by recent single-image hand modeling techniques, they lack the capability to capture sufficient details of the 3D hand mesh. This defici…
Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting
Wentao Bao, Lele Chen, Libing Zeng +4
Hand trajectory forecasting from egocentric views is crucial for enabling a prompt understanding of human intentions when interacting with AR/VR systems. However, existing methods…
Harnessing Low-Frequency Neural Fields for Few-Shot View Synthesis
Liangchen Song, Zhong Li, Xuan Gong +4
Neural Radiance Fields (NeRF) have led to breakthroughs in the novel view synthesis problem. Positional Encoding (P.E.) is a critical factor that brings the impressive performance…
NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields
Liangchen Song, Anpei Chen, Zhong Li +5
Visually exploring in a real-world 4D spatiotemporal space freely in VR has been a long-term quest. The task is especially appealing when only a few or even single RGB cameras are…
NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field
Zhong Li, Liangchen Song, Celong Liu +2
In this paper, we present an efficient and robust deep learning solution for novel view synthesis of complex scenes. In our approach, a 3D scene is represented as a light field, i.…
RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions from Monocular RGBD Stream
Zhuo Su, Lan Xu, Dawei Zhong +4
High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applic…
PoP-Net: Pose over Parts Network for Multi-Person 3D Pose Estimation from a Depth Image
Yuliang Guo, Zhong Li, Zekun Li +3
In this paper, a real-time method called PoP-Net is proposed to predict multi-person 3D poses from a depth image. PoP-Net learns to predict bottom-up part representations and top-d…
Talking-head Generation with Rhythmic Head Motion
Lele Chen, Guofeng Cui, Celong Liu +4
When people deliver a speech, they naturally move heads, and this rhythmic head motion conveys prosodic information. However, generating a lip-synced video while moving head natura…
4D Human Body Correspondences from Panoramic Depth Maps
Zhong Li, Minye Wu, Wangyiteng Zhou +1
The availability of affordable 3D full body reconstruction systems has given rise to free-viewpoint video (FVV) of human shapes. Most existing solutions produce temporally uncorrel…
Robust 3D Human Motion Reconstruction Via Dynamic Template Construction
Zhong Li, Yu Ji, Wei Yang +2
In multi-view human body capture systems, the recovered 3D geometry or even the acquired imagery data can be heavily corrupted due to occlusions, noise, limited field of- view, etc…