no code implementations • 24 Dec 2024 • Hongjie Li, Hong-Xing Yu, Jiaman Li, Jiajun Wu
Human-scene interaction (HSI) generation is crucial for applications in embodied AI, virtual reality, and robotics.
no code implementations • 27 Nov 2024 • Jiaman Li, C. Karen Liu, Jiajun Wu
Estimating 3D motion from 2D observations is a long-standing research challenge.
no code implementations • 25 Jun 2024 • Zhen Wu, Jiaman Li, Pei Xu, C. Karen Liu
Our experiments demonstrate the effectiveness of our system in synthesizing realistic interactions with diverse objects in complex environments, highlighting its potential for real-world applications.
Common Sense Reasoning
Human-Object Interaction Detection
+5
no code implementations • 6 Dec 2023 • Jiaman Li, Alexander Clegg, Roozbeh Mottaghi, Jiajun Wu, Xavier Puig, C. Karen Liu
We demonstrate that our learned interaction module can synthesize realistic human-object interactions, adhering to provided textual descriptions and sparse waypoint conditions.
no code implementations • 28 Sep 2023 • Jiaman Li, Jiajun Wu, C. Karen Liu
We propose Object MOtion guided human MOtion synthesis (OMOMO), a conditional diffusion framework that can generate full-body manipulation behaviors from only the object motion.
1 code implementation • 15 May 2023 • Mark Endo, Joy Hsu, Jiaman Li, Jiajun Wu
In order to build artificial intelligence systems that can perceive and reason with human behavior in the real world, we must first design models that conduct complex spatio-temporal reasoning over motion sequences.
1 code implementation • CVPR 2023 • Joao Pedro Araujo, Jiaman Li, Karthik Vetrivel, Rishi Agarwal, Deepak Gopinath, Jiajun Wu, Alexander Clegg, C. Karen Liu
Leveraging our dataset, the model learns to use ego-centric scene information to achieve nontrivial reaching tasks in the context of complex 3D scenes.
no code implementations • 4 Jan 2023 • Sifan Ye, Yixing Wang, Jiaman Li, Dennis Park, C. Karen Liu, Huazhe Xu, Jiajun Wu
Large-scale capture of human motion with diverse, complex scenes, while immensely useful, is often considered prohibitively costly.
Ranked #3 on
3D Semantic Scene Completion
on PRO-teXt
2D Semantic Segmentation task 1 (8 classes)
3D Semantic Scene Completion
+1
1 code implementation • CVPR 2023 • Jiaman Li, C. Karen Liu, Jiajun Wu
In addition, collecting large-scale, high-quality datasets with paired egocentric videos and 3D human motions requires accurate motion capture devices, which often limit the variety of scenes in the videos to lab-like environments.
1 code implementation • 20 Apr 2022 • Yang Zheng, Yanchao Yang, Kaichun Mo, Jiaman Li, Tao Yu, Yebin Liu, C. Karen Liu, Leonidas J. Guibas
We perform an extensive study of the benefits of leveraging the eye gaze for ego-centric human motion prediction with various state-of-the-art architectures.
no code implementations • 13 Dec 2021 • Zhengfei Kuang, Jiaman Li, Mingming He, Tong Wang, Yajie Zhao
To make the local features aware of the global context and improve their matching accuracy, we introduce DenseGAP, a new solution for efficient Dense correspondence learning with a Graph-structured neural network conditioned on Anchor Points.
no code implementations • 7 Jun 2021 • Jiaman Li, Ruben Villegas, Duygu Ceylan, Jimei Yang, Zhengfei Kuang, Hao Li, Yajie Zhao
We demonstrate the effectiveness of our hierarchical motion variational autoencoder in a variety of tasks including video-based human pose estimation, motion completion from partial observations, and motion synthesis from sparse key-frames.
Ranked #4 on
Motion Synthesis
on LaFAN1
no code implementations • 1 Oct 2020 • Jiaman Li, Zheng-Fei Kuang, Yajie Zhao, Mingming He, Karl Bladin, Hao Li
We also model the joint distribution between identities and expressions, enabling the inference of the full set of personalized blendshapes with dynamic appearances from a single neutral input scan.
no code implementations • 18 Aug 2020 • Jiaman Li, Yihang Yin, Hang Chu, Yi Zhou, Tingwu Wang, Sanja Fidler, Hao Li
We also introduce new evaluation metrics for the quality of synthesized dance motions, and demonstrate that our system can outperform state-of-the-art methods.
4 code implementations • CVPR 2018 • Xavier Puig, Kevin Ra, Marko Boben, Jiaman Li, Tingwu Wang, Sanja Fidler, Antonio Torralba
We then implement the most common atomic (inter)actions in the Unity3D game engine, and use our programs to "drive" an artificial agent to execute tasks in a simulated household environment.
4 code implementations • ICML 2018 • Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger Grosse
The NKN architecture is based on the composition rules for kernels, so that each unit of the network corresponds to a valid kernel.
no code implementations • CVPR 2018 • Ching-Yao Chuang, Jiaman Li, Antonio Torralba, Sanja Fidler
We address the problem of affordance reasoning in diverse scenes that appear in the real world.