no code implementations • 7 Jan 2024 • Xianghui Xie, Xi Wang, Nikos Athanasiou, Bharat Lal Bhatnagar, Chun-Hao P. Huang, Kaichun Mo, Hao Chen, Xia Jia, Zerui Zhang, Liangxian Cui, Xiao Lin, Bingqiao Qian, Jie Xiao, Wenfei Yang, Hyeongjin Nam, Daniel Sungho Jung, Kihoon Kim, Kyoung Mu Lee, Otmar Hilliges, Gerard Pons-Moll
Modeling the interaction between humans and objects has been an emerging research direction in recent years.
no code implementations • CVPR 2023 • Shashank Tripathi, Lea Müller, Chun-Hao P. Huang, Omid Taheri, Michael J. Black, Dimitrios Tzionas
Inspired by biomechanics, we infer the pressure heatmap on the body, the Center of Pressure (CoP) from the heatmap, and the SMPL body's Center of Mass (CoM).
Ranked #1 on 3D Human Pose Estimation on RICH
no code implementations • CVPR 2023 • Hongwei Yi, Chun-Hao P. Huang, Shashank Tripathi, Lea Hering, Justus Thies, Michael J. Black
We propose MIME (Mining Interaction and Movement to infer 3D Environments), which is a generative model of indoor scenes that produces furniture layouts that are consistent with the human movement.
Ranked #2 on Indoor Scene Synthesis on PRO-teXt
2D Semantic Segmentation task 1 (8 classes) 3D Semantic Scene Completion +2
1 code implementation • 28 Sep 2022 • Nitin Saini, Chun-Hao P. Huang, Michael J. Black, Aamir Ahmad
Second, we learn a probability distribution of short human motion sequences ($\sim$1sec) relative to the ground plane and leverage it to disambiguate between the camera and human motion.
2 code implementations • CVPR 2022 • Chun-Hao P. Huang, Hongwei Yi, Markus Höschle, Matvey Safroshkin, Tsvetelina Alexiadis, Senya Polikovsky, Daniel Scharstein, Michael J. Black
We capture a new dataset called RICH for "Real scenes, Interaction, Contact and Humans."
1 code implementation • CVPR 2022 • Vasileios Choutas, Lea Muller, Chun-Hao P. Huang, Siyu Tang, Dimitrios Tzionas, Michael J. Black
Since paired data with images and 3D body shape are rare, we exploit two sources of information: (1) we collect internet images of diverse "fashion" models together with a small set of anthropometric measurements; (2) we collect linguistic shape attributes for a wide range of 3D body meshes and the model images.
Ranked #6 on 3D Human Shape Estimation on SSP-3D
1 code implementation • CVPR 2022 • Hongwei Yi, Chun-Hao P. Huang, Dimitrios Tzionas, Muhammed Kocabas, Mohamed Hassan, Siyu Tang, Justus Thies, Michael J. Black
In fact, we demonstrate that these human-scene interactions (HSIs) can be leveraged to improve the 3D reconstruction of a scene from a monocular RGB video.
1 code implementation • ICCV 2021 • Muhammed Kocabas, Chun-Hao P. Huang, Joachim Tesch, Lea Müller, Otmar Hilliges, Michael J. Black
We then train a novel network that concatenates the camera calibration to the image features and uses these together to regress 3D body shape and pose.
Ranked #1 on 3D Multi-Person Pose Estimation on AGORA
1 code implementation • CVPR 2021 • Priyanka Patel, Chun-Hao P. Huang, Joachim Tesch, David T. Hoffmann, Shashank Tripathi, Michael J. Black
Additionally, we fine-tune methods on AGORA and show improved performance on both AGORA and 3DPW, confirming the realism of the dataset.
1 code implementation • ICCV 2021 • Muhammed Kocabas, Chun-Hao P. Huang, Otmar Hilliges, Michael J. Black
Despite significant progress, we show that state of the art 3D human pose and shape estimation methods remain sensitive to partial occlusion and can produce dramatically wrong predictions although much of the body is observable.
Ranked #2 on 3D Multi-Person Pose Estimation on AGORA
3D human pose and shape estimation 3D Multi-Person Pose Estimation
1 code implementation • CVPR 2021 • Lea Müller, Ahmed A. A. Osman, Siyu Tang, Chun-Hao P. Huang, Michael J. Black
Third, we develop a novel HPS optimization method, SMPLify-XMC, that includes contact constraints and uses the known 3DCP body pose during fitting to create near ground-truth poses for MTP images.
Ranked #73 on 3D Human Pose Estimation on 3DPW (MPJPE metric)