124 citations · 475 across the 20 of their papers we have counts for
20 papers · 1 filter
Synthesizing Physically Plausible Human Motions in 3D Scenes
Liang Pan, Jingbo Wang, Buzhen Huang +4
We present a physics-based character control framework for synthesizing human-scene interactions. Recent advances adopt physics simulation to mitigate artifacts produced by data-dr…
DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering
Wei Cheng, Ruixiang Chen, Wanqi Yin +18
Realistic human-centric rendering plays a key role in both computer vision and computer graphics. Rapid progress has been made in the algorithm aspect over the years, yet existing…
Interactive Character Control with Auto-Regressive Motion Diffusion Models
Yi Shi, Jingbo Wang, Xuekun Jiang +3
Real-time character control is an essential component for interactive experiences, with a broad range of applications, including physics simulations, video games, and virtual reali…
Interactive Segment Anything NeRF with Feature Imitation
Xiaokang Chen, Jiaxiang Tang, Diwen Wan +2
This paper investigates the potential of enhancing Neural Radiance Fields (NeRF) with semantics to expand their applications. Although NeRF has been proven useful in real-world app…
Task-Oriented Human-Object Interactions Generation with Implicit Neural Representations
Quanzhou Li, Jingbo Wang, Chen Change Loy +1
Digital human motion synthesis is a vibrant research field with applications in movies, AR/VR, and video games. Whereas methods were proposed to generate natural and realistic huma…
Towards Diverse and Natural Scene-aware 3D Human Motion Synthesis
Jingbo Wang, Yu Rong, Jingyuan Liu +3
The ability to synthesize long-term human motion sequences in real-world scenes can facilitate numerous applications. Previous approaches for scene-aware motion synthesis are const…
Compressible-composable NeRF via Rank-residual Decomposition
Jiaxiang Tang, Xiaokang Chen, Jingbo Wang +1
Neural Radiance Field (NeRF) has emerged as a compelling method to represent 3D objects and scenes for photo-realistic rendering. However, its implicit representation causes diffic…
Fashionformer: A simple, Effective and Unified Baseline for Human Fashion Segmentation and Recognition
Shilin Xu, Xiangtai Li, Jingbo Wang +3
Human fashion understanding is one crucial computer vision task since it has comprehensive information for real-world applications. This focus on joint human fashion segmentation a…
Point Scene Understanding via Disentangled Instance Mesh Reconstruction
Jiaxiang Tang, Xiaokang Chen, Jingbo Wang +1
Semantic scene reconstruction from point cloud is an essential and challenging task for 3D scene understanding. This task requires not only to recognize each instance in the scene,…
Not All Voxels Are Equal: Semantic Scene Completion from the Point-Voxel Perspective
Xiaokang Chen, Jiaxiang Tang, Jingbo Wang +1
We revisit Semantic Scene Completion (SSC), a useful task to predict the semantic and occupancy representation of 3D scenes, in this paper. A number of methods for this task are al…
Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements
Yu Rong, Jingbo Wang, Ziwei Liu +1
3D interacting hand reconstruction is essential to facilitate human-machine interaction and human behaviors understanding. Previous works in this field either rely on auxiliary inp…
Scene-aware Generative Network for Human Motion Synthesis
Jingbo Wang, Sijie Yan, Bo Dai +1
We revisit human motion synthesis, a task useful in various real world applications, in this paper. Whereas a number of methods have been developed previously for this task, they a…
Malleable 2.5D Convolution: Learning Receptive Fields along the Depth-axis for RGB-D Scene Parsing
Yajie Xing, Jingbo Wang, Gang Zeng
Depth data provide geometric information that can bring progress in RGB-D scene parsing tasks. Several recent works propose RGB-D convolution operators that construct receptive fie…
Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
Xiaokang Chen, Kwan-Yee Lin, Jingbo Wang +4
Depth information has proven to be a useful cue in the semantic segmentation of RGB-D images for providing a geometric counterpart to the RGB representation. Most existing works si…
Motion Guided 3D Pose Estimation from Videos
Jingbo Wang, Sijie Yan, Yuanjun Xiong +1
We propose a new loss function, called motion loss, for the problem of monocular 3D Human pose estimation from 2D pose. In computing motion loss, a simple yet effective representat…
BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation
Changqian Yu, Changxin Gao, Jingbo Wang +3
The low-level details and high-level semantics are both essential to the semantic segmentation task. However, to speed up the model inference, current approaches almost always sacr…
Context Prior for Scene Segmentation
Changqian Yu, Jingbo Wang, Changxin Gao +3
Recent works have widely explored the contextual dependencies to achieve more accurate segmentation results. However, most approaches rarely distinguish different types of contextu…
An End-to-End Network for Panoptic Segmentation
Huanyu Liu, Chao Peng, Changqian Yu +4
Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic. Traditionally, the existing app…
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
Changqian Yu, Jingbo Wang, Chao Peng +3
Semantic segmentation requires both rich spatial information and sizeable receptive field. However, modern approaches usually compromise spatial resolution to achieve real-time inf…
Learning a Discriminative Feature Network for Semantic Segmentation
Changqian Yu, Jingbo Wang, Chao Peng +3
Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction. To tackle these two problems, w…