656 citations · 1.1k across the 55 of their papers we have counts for
55 papers
TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting
Rohan Choudhury, Kris Kitani, Laszlo A. Jeni
Existing volumetric methods for predicting 3D human pose estimation are accurate, but computationally expensive and optimized for single time-step prediction. We present TEMPO, an…
Joint Metrics Matter: A Better Standard for Trajectory Forecasting
Erica Weng, Hana Hoshino, Deva Ramanan +1
Multi-modal trajectory forecasting methods commonly evaluate using single-agent metrics (marginal metrics), such as minimum Average Displacement Error (ADE) and Final Displacement…
HERD: Continuous Human-to-Robot Evolution for Learning from Human Demonstration
Xingyu Liu, Deepak Pathak, Kris M. Kitani
The ability to learn from human demonstration endows robots with the ability to automate various tasks. However, directly learning from human demonstration is challenging since the…
From Universal Humanoid Control to Automatic Physically Valid Character Creation
Zhengyi Luo, Ye Yuan, Kris M. Kitani
Automatically designing virtual humans and humanoids holds great potential in aiding the character creation process in games, movies, and robots. In some cases, a character creator…
Cost-Aware Evaluation and Model Scaling for LiDAR-Based 3D Object Detection
Xiaofang Wang, Kris M. Kitani
Considerable research effort has been devoted to LiDAR-based 3D object detection and empirical performance has been significantly improved. While progress has been encouraging, we…
Online No-regret Model-Based Meta RL for Personalized Navigation
Yuda Song, Ye Yuan, Wen Sun +1
The interaction between a vehicle navigation system and the driver of the vehicle can be formulated as a model-based reinforcement learning problem, where the navigation systems (a…
REvolveR: Continuous Evolutionary Models for Robot-to-robot Policy Transfer
Xingyu Liu, Deepak Pathak, Kris M. Kitani
A popular paradigm in robotic learning is to train a policy from scratch for every new robot. This is not only inefficient but also often impractical for complex robots. In this wo…
V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects
Xingyu Liu, Kris M. Kitani
Manipulating articulated objects requires multiple robot arms in general. It is challenging to enable multiple robot arms to collaboratively complete manipulation tasks on articula…
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation
Khoa Vo, Hyekang Joo, Kashu Yamazaki +4
Humans typically perceive the establishment of an action in a video through the interaction between an actor and the surrounding environment. An action only starts when the main ac…
Sequential Voting with Relational Box Fields for Active Object Detection
Qichen Fu, Xingyu Liu, Kris M. Kitani
A key component of understanding hand-object interactions is the ability to identify the active object -- the object that is being manipulated by the human hand. In order to accura…
Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
Ye Yuan, Yuda Song, Zhengyi Luo +2
An agent's functionality is largely determined by its design, i.e., skeletal structure and joint attributes (e.g., length, size, strength). However, finding the optimal agent desig…
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation
Xingyu Liu, Shun Iwase, Kris M. Kitani
We present KDFNet, a novel method for 6D object pose estimation from RGB images. To handle occlusion, many recent works have proposed to localize 2D keypoints through pixel-wise vo…
StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation
Xingyu Liu, Shun Iwase, Kris M. Kitani
We present a large-scale stereo RGB image object pose estimation dataset named the dataset. The dataset is designed to address challenging cases such as obje…
No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency
S. Alireza Golestaneh, Saba Dadsetan, Kris M. Kitani
The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the perceptual image quality in accordance with subjective evaluations, it is a complex and unsolved probl…
Neighborhood-Aware Neural Architecture Search
Xiaofang Wang, Shengcao Cao, Mengtian Li +1
Existing neural architecture search (NAS) methods often return an architecture with good search performance but generalizes poorly to the test setting. To achieve better generaliza…
RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering
Shun Iwase, Xingyu Liu, Rawal Khirodkar +2
We present RePOSE, a fast iterative refinement method for 6D object pose estimation. Prior methods perform refinement by feeding zoomed-in input and rendered RGB images into a CNN…
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…
Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models
Xiaofang Wang, Dan Kondratyuk, Eric Christiansen +3
Committee-based models (ensembles or cascades) construct models by combining existing pre-trained ones. While ensembles and cascades are well-known techniques that were proposed be…
Importance of Self-Consistency in Active Learning for Semantic Segmentation
S. Alireza Golestaneh, Kris M. Kitani
We address the task of active learning in the context of semantic segmentation and show that self-consistency can be a powerful source of self-supervision to greatly improve the pe…
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…
AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification
Xiaofang Wang, Xuehan Xiong, Maxim Neumann +5
Convolutional operations have two limitations: (1) do not explicitly model where to focus as the same filter is applied to all the positions, and (2) are unsuitable for modeling lo…
Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimation
Mariko Isogawa, Ye Yuan, Matthew O'Toole +1
We describe a method for 3D human pose estimation from transient images (i.e., a 3D spatio-temporal histogram of photons) acquired by an optical non-line-of-sight (NLOS) imaging sy…
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…
DLow: Diversifying Latent Flows for Diverse Human Motion Prediction
Ye Yuan, Kris Kitani
Deep generative models are often used for human motion prediction as they are able to model multi-modal data distributions and characterize diverse human behavior. While much care…