In-depth look at our work.
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.Conference: European Conference on Computer Vision (ECCV 2024)
Authors:Marko Mihajlovic, Sergey Prokudin, Siyu Tang, Robert Maier, Federica Bogo, Tony Tung, Edmond Boyer
SplatFields regularizes 3D gaussian splats for sparse 3D and 4D reconstruction.Conference: Conference on Computer Vision and Pattern Recognition (CVPR 2024)
Authors:Yan Zhang, Sergey Prokudin, Marko Mihajlovic, Qianli Ma, Siyu Tang
DOMA is an implicit motion field modeled by a spatiotemporal SIREN network. The learned motion field can predict how novel points move in the same field.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...
