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20182024
most citedDynamics-Regulated Kinematic Policy for Egocentric Pose Estimation

38 citations · 156 across the 18 of their papers we have counts for

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13 papers · 1 filter

cs.CV2024★ 1 cited

Harmony4D: A Video Dataset for In-The-Wild Close Human Interactions

Rawal Khirodkar, Jyun-Ting Song, Jinkun Cao +2

Understanding how humans interact with each other is key to building realistic multi-human virtual reality systems. This area remains relatively unexplored due to the lack of large…

cs.CV2024

Real-Time Simulated Avatar from Head-Mounted Sensors

Zhengyi Luo, Jinkun Cao, Rawal Khirodkar +4

We present SimXR, a method for controlling a simulated avatar from information (headset pose and cameras) obtained from AR / VR headsets. Due to the challenging viewpoint of head-m…

cs.CV2023★ 20 cited

Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98

We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…

cs.CV2023★ 4 cited

Universal Humanoid Motion Representations for Physics-Based Control

Zhengyi Luo, Jinkun Cao, Josh Merel +4

We present a universal motion representation that encompasses a comprehensive range of motor skills for physics-based humanoid control. Due to the high dimensionality of humanoids…

cs.CV2023★ 1 cited

Perpetual Humanoid Control for Real-time Simulated Avatars

Zhengyi Luo, Jinkun Cao, Alexander Winkler +2

We present a physics-based humanoid controller that achieves high-fidelity motion imitation and fault-tolerant behavior in the presence of noisy input (e.g. pose estimates from vid…

cs.CV2023★ 1 cited

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

Davis Rempe, Zhengyi Luo, Xue Bin Peng +5

We introduce a method for generating realistic pedestrian trajectories and full-body animations that can be controlled to meet user-defined goals. We draw on recent advances in gui…

cs.CV2022★ 19 cited

Embodied Scene-aware Human Pose Estimation

Zhengyi Luo, Shun Iwase, Ye Yuan +1

We propose embodied scene-aware human pose estimation where we estimate 3D poses based on a simulated agent's proprioception and scene awareness, along with external third-person o…

cs.CV2021★ 38 cited

Dynamics-Regulated Kinematic Policy for Egocentric Pose Estimation

Zhengyi Luo, Ryo Hachiuma, Ye Yuan +1

We propose a method for object-aware 3D egocentric pose estimation that tightly integrates kinematics modeling, dynamics modeling, and scene object information. Unlike prior kinema…

cs.CV2020★ 4 cited

Kinematics-Guided Reinforcement Learning for Object-Aware 3D Ego-Pose Estimation

Zhengyi Luo, Ryo Hachiuma, Ye Yuan +2

We propose a method for incorporating object interaction and human body dynamics into the task of 3D ego-pose estimation using a head-mounted camera. We use a kinematics model of t…

cs.CV2020★ 10 cited

3D Human Motion Estimation via Motion Compression and Refinement

Zhengyi Luo, S. Alireza Golestaneh, Kris M. Kitani

We develop a technique for generating smooth and accurate 3D human pose and motion estimates from RGB video sequences. Our method, which we call Motion Estimation via Variational A…

cs.CV2020★ 33 cited

Learning Shape Representations for Clothing Variations in Person Re-Identification

Yu-Jhe Li, Zhengyi Luo, Xinshuo Weng +1

Person re-identification (re-ID) aims to recognize instances of the same person contained in multiple images taken across different cameras. Existing methods for re-ID tend to rely…

cs.CV2018★ 8 cited

Cross-Domain 3D Equivariant Image Embeddings

Carlos Esteves, Avneesh Sud, Zhengyi Luo +2

Spherical convolutional networks have been introduced recently as tools to learn powerful feature representations of 3D shapes. Spherical CNNs are equivariant to 3D rotations makin…

cs.CV2018★ 8 cited

Cloud Chaser: Real Time Deep Learning Computer Vision on Low Computing Power Devices

Zhengyi Luo, Austin Small, Liam Dugan +1

Internet of Things(IoT) devices, mobile phones, and robotic systems are often denied the power of deep learning algorithms due to their limited computing power. However, to provide…