In-depth look at our work.
Conference: SIGGRAPH 2025 Conference Track
Authors:Mingyang Song, Yang Zhang, Marko Mihajlovic, Siyu Tang, Markus Gross, Tunc Aydin
We combine splines, a classical tool from applied mathematics, with implicit Coordinate Neural Networks to model deformation fields, achieving strong performance across multiple datasets. The explicit regularization from spline interpolation enhances spatial coherency in challenging scenarios. We further introduce a metric based on Moran's I to quantitatively evaluate spatial coherence.Conference: SIGGRAPH 2025 Conference Track
Authors:Zinuo You, Stamatios Georgoulis, Anpei Chen, Siyu Tang, Dengxin Dai
GaVS reformulates video stabilization task with feed-forward 3DGS reconstruction, ensuring robustness to diverse motions, full-frame rendering and high geometry consistency.Conference: SIGGRAPH 2025 Conference Track
Authors:Shaofei Wang, Tomas Simon, Igor Santesteban, Timur Bagautdinov, Junxuan Li, Vasu Agrawal, Fabian Prada, Shoou-I Yu, Pace Nalbone, Matt Gramlich, Roman Lubachersky, Chenglei Wu, Javier Romero, Jason Saragih, Michael Zollhoefer, Andreas Geiger, Siyu Tang, Shunsuke Saito
RFGCA learns high-fidelity relightable and drivable full-body avatars from light stage captures.Conference: International Conference on Computer Vision (ICCV 2025)
Authors:Gen Li, Yutong Chen*, Yiqian Wu*, Kaifeng Zhao*, Marc Pollefeys, Siyu Tang (*equal contribution)
EgoM2P: A large-scale egocentric multimodal and multitask model, pretrained on eight extensive egocentric datasets. It incorporates four modalities—RGB and depth video, gaze dynamics, and camera trajectories—to handle challenging tasks like monocular egocentric depth estimation, camera tracking, gaze estimation, and conditional egocentric video synthesisConference: SIGGRAPH 2025 Conference Track
Authors:Yiqian Wu, Malte Prinzler, Xiaogang Jin, Siyu Tang
AnimPortrait3D is a novel method for text-based, realistic, animatable 3DGS avatar generation with morphable model alignment.Conference: The 12th International Conference on 3D Vision (3DV 2025)
Authors:Deheng Zhang*, Jingyu Wang*, Shaofei Wang, Marko Mihajlovic, Sergey Prokudin, Hendrik P.A. Lensch, Siyu Tang (*equal contribution)
We present RISE-SDF, a method for reconstructing the geometry and material of glossy objects while achieving high-quality relighting.Conference: The Thirteenth International Conference on Learning Representations (ICLR 2025) spotlight presentation
Authors:Kaifeng Zhao, Gen Li, Siyu Tang
DART is a Diffusion-based Autoregressive motion model for Real-time Text-driven motion control. Furthermore, DART enables various motion generation applications with spatial constraints and goals, including motion in-between, waypoint goal reaching, and human-scene interaction generation.Conference: The Thirteenth International Conference on Learning Representations (ICLR 2025) spotlight presentation
Authors:Yutong Chen, Marko Mihajlovic, Xiyi Chen, Yiming Wang, Sergey Prokudin, Siyu Tang
We analyze the performance of novel view synthesis methods in challenging out-of-distribution (OOD) camera views and introduce SplatFormer, a data-driven 3D transformer designed to refine 3D Gaussian splatting primitives for improved quality in extreme camera scenarios.Here’s what we've been up to recently.
We have seven papers accepted at CVPR 2024:RoHM: Robust Human Motion Reconstruction via Diffusion (oral presentation)EgoGen: An Egocentric Synthetic Data Generator (oral presentation)DNO: Optimizing Diffusion Noise Can Serve As Universal Motion PriorsMorphable Diffusion: 3D-Consistent Diffusion for...
We have five papers accepted at ICCV 2023:Dynamic Point Fields: Towards Efficient and Scalable Dynamic Surface Representations (oral presentation)EgoHMR: Probabilistic Human Mesh Recovery in 3D Scenes from Egocentric Views (oral presentation)GMD: Controllable Human Motion Synthesis via Guided...
