19 citations · 62 across the 16 of their papers we have counts for
21 papers
SmallGS: Gaussian Splatting-based Camera Pose Estimation for Small-Baseline Videos
Yuxin Yao, Yan Zhang, Zhening Huang +1
Dynamic videos with small baseline motions are ubiquitous in daily life, especially on social media. However, these videos present a challenge to existing pose estimation framework…
Degrees of Freedom Matter: Inferring Dynamics from Point Trajectories
Yan Zhang, Sergey Prokudin, Marko Mihajlovic +2
Understanding the dynamics of generic 3D scenes is fundamentally challenging in computer vision, essential in enhancing applications related to scene reconstruction, motion trackin…
RELI11D: A Comprehensive Multimodal Human Motion Dataset and Method
Ming Yan, Yan Zhang, Shuqiang Cai +8
Comprehensive capturing of human motions requires both accurate captures of complex poses and precise localization of the human within scenes. Most of the HPE datasets and methods…
EgoGen: An Egocentric Synthetic Data Generator
Gen Li, Kaifeng Zhao, Siwei Zhang +5
Understanding the world in first-person view is fundamental in Augmented Reality (AR). This immersive perspective brings dramatic visual changes and unique challenges compared to t…
Synthesizing Diverse Human Motions in 3D Indoor Scenes
Kaifeng Zhao, Yan Zhang, Shaofei Wang +2
We present a novel method for populating 3D indoor scenes with virtual humans that can navigate in the environment and interact with objects in a realistic manner. Existing approac…
Probabilistic Human Mesh Recovery in 3D Scenes from Egocentric Views
Siwei Zhang, Qianli Ma, Yan Zhang +3
Automatic perception of human behaviors during social interactions is crucial for AR/VR applications, and an essential component is estimation of plausible 3D human pose and shape…
Compositional Human-Scene Interaction Synthesis with Semantic Control
Kaifeng Zhao, Shaofei Wang, Yan Zhang +2
Synthesizing natural interactions between virtual humans and their 3D environments is critical for numerous applications, such as computer games and AR/VR experiences. Our goal is…
SAGA: Stochastic Whole-Body Grasping with Contact
Yan Wu, Jiahao Wang, Yan Zhang +4
The synthesis of human grasping has numerous applications including AR/VR, video games and robotics. While methods have been proposed to generate realistic hand-object interaction…
The Wanderings of Odysseus in 3D Scenes
Yan Zhang, Siyu Tang
Our goal is to populate digital environments, in which digital humans have diverse body shapes, move perpetually, and have plausible body-scene contact. The core challenge is to ge…
EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devices
Siwei Zhang, Qianli Ma, Yan Zhang +5
Understanding social interactions from egocentric views is crucial for many applications, ranging from assistive robotics to AR/VR. Key to reasoning about interactions is to unders…
Learning Motion Priors for 4D Human Body Capture in 3D Scenes
Siwei Zhang, Yan Zhang, Federica Bogo +2
Recovering high-quality 3D human motion in complex scenes from monocular videos is important for many applications, ranging from AR/VR to robotics. However, capturing realistic hum…
LEAP: Learning Articulated Occupancy of People
Marko Mihajlovic, Yan Zhang, Michael J. Black +1
Substantial progress has been made on modeling rigid 3D objects using deep implicit representations. Yet, extending these methods to learn neural models of human shape is still in…
We are More than Our Joints: Predicting how 3D Bodies Move
Yan Zhang, Michael J. Black, Siyu Tang
A key step towards understanding human behavior is the prediction of 3D human motion. Successful solutions have many applications in human tracking, HCI, and graphics. Most previou…
4D Human Body Capture from Egocentric Video via 3D Scene Grounding
Miao Liu, Dexin Yang, Yan Zhang +3
We introduce a novel task of reconstructing a time series of second-person 3D human body meshes from monocular egocentric videos. The unique viewpoint and rapid embodied camera mot…
PLACE: Proximity Learning of Articulation and Contact in 3D Environments
Siwei Zhang, Yan Zhang, Qianli Ma +2
High fidelity digital 3D environments have been proposed in recent years, however, it remains extremely challenging to automatically equip such environment with realistic human bod…
Grasping Field: Learning Implicit Representations for Human Grasps
Korrawe Karunratanakul, Jinlong Yang, Yan Zhang +3
Robotic grasping of house-hold objects has made remarkable progress in recent years. Yet, human grasps are still difficult to synthesize realistically. There are several key reason…
Perpetual Motion: Generating Unbounded Human Motion
Yan Zhang, Michael J. Black, Siyu Tang
The modeling of human motion using machine learning methods has been widely studied. In essence it is a time-series modeling problem involving predicting how a person will move in…
Generating 3D People in Scenes without People
Yan Zhang, Mohamed Hassan, Heiko Neumann +2
We present a fully automatic system that takes a 3D scene and generates plausible 3D human bodies that are posed naturally in that 3D scene. Given a 3D scene without people, humans…
Frontal Low-rank Random Tensors for Fine-grained Action Segmentation
Yan Zhang, Krikamol Muandet, Qianli Ma +2
Fine-grained action segmentation in long untrimmed videos is an important task for many applications such as surveillance, robotics, and human-computer interaction. To understand s…
An Empirical Study towards Understanding How Deep Convolutional Nets Recognize Falls
Yan Zhang, Heiko Neumann
Detecting unintended falls is essential for ambient intelligence and healthcare of elderly people living alone. In recent years, deep convolutional nets are widely used in human ac…
Local Temporal Bilinear Pooling for Fine-grained Action Parsing
Yan Zhang, Siyu Tang, Krikamol Muandet +2
Fine-grained temporal action parsing is important in many applications, such as daily activity understanding, human motion analysis, surgical robotics and others requiring subtle a…