In-depth look at our work.
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)
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)
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.Conference: Conference on Computer Vision and Pattern Recognition (CVPR 2024)
Authors:Korrawe Karunratanakul, Konpat Preechakul, Emre Aksan, Thabo Beeler, Supasorn Suwajanakorn, Siyu Tang
Diffusion Noise Optimization (DNO) can leverage the existing human motion diffusion models as universal motion priors. We demonstrate its capability in the motion editing tasks where DNO can preserve the content of the original model and accommodates a diverse range of editing modes, including changing trajectory, pose, joint location, and avoiding newly added obstacles.Conference: Conference on Computer Vision and Pattern Recognition (CVPR 2024) oral presentation
Authors:Siwei Zhang, Bharat Lal Bhatnagar, Yuanlu Xu, Alexander Winkler, Petr Kadlecek, Siyu Tang, Federica Bogo
Conditioned on noisy and occluded input data, RoHM reconstructs complete, plausible motions in consistent global coordinates.Conference: Conference on Computer Vision and Pattern Recognition (CVPR 2024) oral presentation
Authors:Gen Li, Kaifeng Zhao, Siwei Zhang, Xiaozhong Lyu, Mihai Dusmanu, Yan Zhang, Marc Pollefeys, Siyu Tang
EgoGen is new synthetic data generator that can produce accurate and rich ground-truth training data for egocentric perception tasks.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...
