114 citations · 130 across the 19 of their papers we have counts for
19 papers
tttLRM: Test-Time Training for Long Context and Autoregressive 3D Reconstruction
Chen Wang, Hao Tan, Wang Yifan +6
We propose tttLRM, a novel large 3D reconstruction model that leverages a Test-Time Training (TTT) layer to enable long-context, autoregressive 3D reconstruction with linear comput…
PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generation
Chen Wang, Chuhao Chen, Yiming Huang +4
Existing video generation models excel at producing photo-realistic videos from text or images, but often lack physical plausibility and 3D controllability. To overcome these limit…
Pixie: Fast and Generalizable Supervised Learning of 3D Physics from Pixels
Long Le, Ryan Lucas, Chen Wang +4
Inferring the physical properties of 3D scenes from visual information is a critical yet challenging task for creating interactive and realistic virtual worlds. While humans intuit…
ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking
Tingyang Zhang, Chen Wang, Zhiyang Dou +4
We propose ProTracker, a novel framework for accurate and robust long-term dense tracking of arbitrary points in videos. Previous methods relying on global cost volumes effectively…
DICE: End-to-end Deformation Capture of Hand-Face Interactions from a Single Image
Qingxuan Wu, Zhiyang Dou, Sirui Xu +11
Reconstructing 3D hand-face interactions with deformations from a single image is a challenging yet crucial task with broad applications in AR, VR, and gaming. The challenges stem…
GECO: Generative Image-to-3D within a SECOnd
Chen Wang, Jiatao Gu, Xiaoxiao Long +2
Recent years have seen significant advancements in 3D generation. While methods like score distillation achieve impressive results, they often require extensive per-scene optimizat…
Digging into Depth Priors for Outdoor Neural Radiance Fields
Chen Wang, Jiadai Sun, Lina Liu +5
Neural Radiance Fields (NeRF) have demonstrated impressive performance in vision and graphics tasks, such as novel view synthesis and immersive reality. However, the shape-radiance…
Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shape
Jiacong Xu, Yi Zhang, Jiawei Peng +17
Accurately estimating the 3D pose and shape is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife c…
SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation
Yiqing Wang, Zihan Li, Jieru Mei +7
Recent advancements in large-scale Vision Transformers have made significant strides in improving pre-trained models for medical image segmentation. However, these methods face a n…
DreamEditor: Text-Driven 3D Scene Editing with Neural Fields
Jingyu Zhuang, Chen Wang, Lingjie Liu +2
Neural fields have achieved impressive advancements in view synthesis and scene reconstruction. However, editing these neural fields remains challenging due to the implicit encodin…
PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas
Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo +3
Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (V…
VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthesis
Yuan-Chen Guo, Yan-Pei Cao, Chen Wang +4
With the emergence of neural radiance fields (NeRFs), view synthesis quality has reached an unprecedented level. Compared to traditional mesh-based assets, this volumetric represen…
Benchmarking Robustness in Neural Radiance Fields
Chen Wang, Angtian Wang, Junbo Li +2
Neural Radiance Field (NeRF) has demonstrated excellent quality in novel view synthesis, thanks to its ability to model 3D object geometries in a concise formulation. However, curr…
StructNeRF: Neural Radiance Fields for Indoor Scenes with Structural Hints
Zheng Chen, Chen Wang, Yuan-Chen Guo +1
Neural Radiance Fields (NeRF) achieve photo-realistic view synthesis with densely captured input images. However, the geometry of NeRF is extremely under-constrained given sparse v…
DeepPortraitDrawing: Generating Human Body Images from Freehand Sketches
Xian Wu, Chen Wang, Hongbo Fu +3
Researchers have explored various ways to generate realistic images from freehand sketches, e.g., for objects and human faces. However, how to generate realistic human body images…
On Rotation Gains Within and Beyond Perceptual Limitations for Seated VR
Chen Wang, Song-Hai Zhang, Yizhuo Zhang +2
Head tracking in head-mounted displays (HMDs) enables users to explore a 360-degree virtual scene with free head movements. However, for seated use of HMDs such as users sitting on…
NeRF-SR: High-Quality Neural Radiance Fields using Supersampling
Chen Wang, Xian Wu, Yuan-Chen Guo +3
We present NeRF-SR, a solution for high-resolution (HR) novel view synthesis with mostly low-resolution (LR) inputs. Our method is built upon Neural Radiance Fields (NeRF) that pre…
Learning Implicit Glyph Shape Representation
Ying-Tian Liu, Yuan-Chen Guo, Yi-Xiao Li +2
In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph…
Learning Purified Feature Representations from Task-irrelevant Labels
Yinghui Li, Chen Wang, Yangning Li +2
Learning an empirically effective model with generalization using limited data is a challenging task for deep neural networks. In this paper, we propose a novel learning framework…