629 citations · 641 across the 16 of their papers we have counts for
18 papers
CoTL: Compact Token Learning for 3D Scene Representation
Han Liang, Sibo Wu, Anpei Chen +1
We present CoTL, a framework that learns a compact set of tokens that preserves scene geometry and appearance from unposed multi-view images. Our encoder compresses the input image…
: 3D Reconstruction via Relative Regression
Congrong Xu, Huachen Gao, Xingyu Chen +3
Recent feed-forward geometry foundation models have demonstrated impressive generalization by recovering depth and poses in a single forward pass. However, these models are typical…
GaussiAnimate: Rig Animatable Categories with Level of Dynamics
Jiaxin Wang, Dongxin Lyu, Zeyu Cai +4
We propose Skelebones, a Scaffold-Skin Rigging System built on three steps: (1) Bones compress temporally consistent Gaussian or mesh sequences into free-form bones with smooth ski…
ConeGS: Error-Guided Densification Using Pixel Cones for Improved Reconstruction With Fewer Primitives
Bartłomiej Baranowski, Stefano Esposito, Patricia Gschoßmann +2
3D Gaussian Splatting (3DGS) achieves state-of-the-art image quality and real-time performance in novel view synthesis but often suffers from a suboptimal spatial distribution of p…
Human3R: Everyone Everywhere All at Once
Yue Chen, Xingyu Chen, Yuxuan Xue +3
We present Human3R, a unified, feed-forward framework for online 4D human-scene reconstruction, in the world frame, from casually captured monocular videos. Unlike previous approac…
TTT3R: 3D Reconstruction as Test-Time Training
Xingyu Chen, Yue Chen, Yuliang Xiu +2
Modern Recurrent Neural Networks have become a competitive architecture for 3D reconstruction due to their linear-time complexity. However, their performance degrades significantly…
GaVS: 3D-Grounded Video Stabilization via Temporally-Consistent Local Reconstruction and Rendering
Zinuo You, Stamatios Georgoulis, Anpei Chen +2
Video stabilization is pivotal for video processing, as it removes unwanted shakiness while preserving the original user motion intent. Existing approaches, depending on the domain…
LoftUp: Learning a Coordinate-Based Feature Upsampler for Vision Foundation Models
Haiwen Huang, Anpei Chen, Volodymyr Havrylov +2
Vision foundation models (VFMs) such as DINOv2 and CLIP have achieved impressive results on various downstream tasks, but their limited feature resolution hampers performance in ap…
GenFusion: Closing the Loop between Reconstruction and Generation via Videos
Sibo Wu, Congrong Xu, Binbin Huang +2
Recently, 3D reconstruction and generation have demonstrated impressive novel view synthesis results, achieving high fidelity and efficiency. However, a notable conditioning gap ca…
Easi3R: Estimating Disentangled Motion from DUSt3R Without Training
Xingyu Chen, Yue Chen, Yuliang Xiu +2
Recent advances in DUSt3R have enabled robust estimation of dense point clouds and camera parameters of static scenes, leveraging Transformer network architectures and direct super…
Feat2GS: Probing Visual Foundation Models with Gaussian Splatting
Yue Chen, Xingyu Chen, Anpei Chen +2
Given that visual foundation models (VFMs) are trained on extensive datasets but often limited to 2D images, a natural question arises: how well do they understand the 3D world? Wi…
Volumetric Surfaces: Representing Fuzzy Geometries with Layered Meshes
Stefano Esposito, Anpei Chen, Christian Reiser +7
High-quality view synthesis relies on volume rendering, splatting, or surface rendering. While surface rendering is typically the fastest, it struggles to accurately model fuzzy ge…
LaRa: Efficient Large-Baseline Radiance Fields
Anpei Chen, Haofei Xu, Stefano Esposito +2
Radiance field methods have achieved photorealistic novel view synthesis and geometry reconstruction. But they are mostly applied in per-scene optimization or small-baseline settin…
2D Gaussian Splatting for Geometrically Accurate Radiance Fields
Binbin Huang, Zehao Yu, Anpei Chen +2
3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However…
NeLF-Pro: Neural Light Field Probes for Multi-Scale Novel View Synthesis
Zinuo You, Andreas Geiger, Anpei Chen
We present NeLF-Pro, a novel representation to model and reconstruct light fields in diverse natural scenes that vary in extent and spatial granularity. In contrast to previous fas…
MuRF: Multi-Baseline Radiance Fields
Haofei Xu, Anpei Chen, Yuedong Chen +5
We present Multi-Baseline Radiance Fields (MuRF), a general feed-forward approach to solving sparse view synthesis under multiple different baseline settings (small and large basel…
GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs
Gege Gao, Weiyang Liu, Anpei Chen +2
As pretrained text-to-image diffusion models become increasingly powerful, recent efforts have been made to distill knowledge from these text-to-image pretrained models for optimiz…
Mip-Splatting: Alias-free 3D Gaussian Splatting
Zehao Yu, Anpei Chen, Binbin Huang +2
Recently, 3D Gaussian Splatting has demonstrated impressive novel view synthesis results, reaching high fidelity and efficiency. However, strong artifacts can be observed when chan…