90 citations · 678 across the 49 of their papers we have counts for
14 papers · 1 filter
GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras
Ye Yuan, Umar Iqbal, Pavlo Molchanov +2
We present an approach for 3D global human mesh recovery from monocular videos recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions and tracks h…
DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion
Peize Sun, Jinkun Cao, Yi Jiang +4
A typical pipeline for multi-object tracking (MOT) is to use a detector for object localization, and following re-identification (re-ID) for object association. This pipeline is pa…
Cross-Domain Adaptive Teacher for Object Detection
Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma +6
We address the task of domain adaptation in object detection, where there is a domain gap between a domain with annotations (source) and a domain of interest without annotations (t…
Ego4D: Around the World in 3,000 Hours of Egocentric Video
Kristen Grauman, Andrew Westbury, Eugene Byrne +82
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outd…
Multi-Echo LiDAR for 3D Object Detection
Yunze Man, Xinshuo Weng, Prasanna Kumar Sivakuma +2
LiDAR sensors can be used to obtain a wide range of measurement signals other than a simple 3D point cloud, and those signals can be leveraged to improve perception tasks like 3D o…
Multi-Modality Task Cascade for 3D Object Detection
Jinhyung Park, Xinshuo Weng, Yunze Man +1
Point clouds and RGB images are naturally complementary modalities for 3D visual understanding - the former provides sparse but accurate locations of points on objects, while the l…
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…
Wide-Baseline Multi-Camera Calibration using Person Re-Identification
Yan Xu, Yu-Jhe Li, Xinshuo Weng +1
We address the problem of estimating the 3D pose of a network of cameras for large-environment wide-baseline scenarios, e.g., cameras for construction sites, sports stadiums, and p…
SimPoE: Simulated Character Control for 3D Human Pose Estimation
Ye Yuan, Shih-En Wei, Tomas Simon +2
Accurate estimation of 3D human motion from monocular video requires modeling both kinematics (body motion without physical forces) and dynamics (motion with physical forces). To d…
Efficient Model Performance Estimation via Feature Histories
Shengcao Cao, Xiaofang Wang, Kris Kitani
An important step in the task of neural network design, such as hyper-parameter optimization (HPO) or neural architecture search (NAS), is the evaluation of a candidate model's per…
Inverse Reinforcement Learning with Explicit Policy Estimates
Navyata Sanghvi, Shinnosuke Usami, Mohit Sharma +2
Various methods for solving the inverse reinforcement learning (IRL) problem have been developed independently in machine learning and economics. In particular, the method of Maxim…
AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting
Ye Yuan, Xinshuo Weng, Yanglan Ou +1
Predicting accurate future trajectories of multiple agents is essential for autonomous systems, but is challenging due to the complex agent interaction and the uncertainty in each…
DeepBLE: Generalizing RSSI-based Localization Across Different Devices
Harsh Agarwal, Navyata Sanghvi, Vivek Roy +1
Accurate smartphone localization (< 1-meter error) for indoor navigation using only RSSI received from a set of BLE beacons remains a challenging problem, due to the inherent noise…
IDOL: Inertial Deep Orientation-Estimation and Localization
Scott Sun, Dennis Melamed, Kris Kitani
Many smartphone applications use inertial measurement units (IMUs) to sense movement, but the use of these sensors for pedestrian localization can be challenging due to their noise…