20 citations · 59 across the 15 of their papers we have counts for
15 papers
Learning Predictive Visuomotor Coordination
Wenqi Jia, Bolin Lai, Miao Liu +2
Understanding and predicting human visuomotor coordination is crucial for applications in robotics, human-computer interaction, and assistive technologies. This work introduces a f…
Human Action Anticipation: A Survey
Bolin Lai, Sam Toyer, Tushar Nagarajan +7
Predicting future human behavior is an increasingly popular topic in computer vision, driven by the interest in applications such as autonomous vehicles, digital assistants and hum…
BEHAVIOR Vision Suite: Customizable Dataset Generation via Simulation
Yunhao Ge, Yihe Tang, Jiashu Xu +20
The systematic evaluation and understanding of computer vision models under varying conditions require large amounts of data with comprehensive and customized labels, which real-wo…
The Audio-Visual Conversational Graph: From an Egocentric-Exocentric Perspective
Wenqi Jia, Miao Liu, Hao Jiang +4
In recent years, the thriving development of research related to egocentric videos has provided a unique perspective for the study of conversational interactions, where both visual…
LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning
Bolin Lai, Xiaoliang Dai, Lawrence Chen +3
Generating instructional images of human daily actions from an egocentric viewpoint serves as a key step towards efficient skill transfer. In this paper, we introduce a novel probl…
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…
Listen to Look into the Future: Audio-Visual Egocentric Gaze Anticipation
Bolin Lai, Fiona Ryan, Wenqi Jia +2
Egocentric gaze anticipation serves as a key building block for the emerging capability of Augmented Reality. Notably, gaze behavior is driven by both visual cues and audio signals…
Werewolf Among Us: A Multimodal Dataset for Modeling Persuasion Behaviors in Social Deduction Games
Bolin Lai, Hongxin Zhang, Miao Liu +6
Persuasion modeling is a key building block for conversational agents. Existing works in this direction are limited to analyzing textual dialogue corpus. We argue that visual signa…
In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation
Bolin Lai, Miao Liu, Fiona Ryan +1
In this paper, we present the first transformer-based model to address the challenging problem of egocentric gaze estimation. We observe that the connection between the global scen…
Generative Adversarial Network for Future Hand Segmentation from Egocentric Video
Wenqi Jia, Miao Liu, James M. Rehg
We introduce the novel problem of anticipating a time series of future hand masks from egocentric video. A key challenge is to model the stochasticity of future head motions, which…
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…
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…
In the Eye of the Beholder: Gaze and Actions in First Person Video
Yin Li, Miao Liu, James M. Rehg
We address the task of jointly determining what a person is doing and where they are looking based on the analysis of video captured by a headworn camera. To facilitate our researc…
Forecasting Human-Object Interaction: Joint Prediction of Motor Attention and Actions in First Person Video
Miao Liu, Siyu Tang, Yin Li +1
We address the challenging task of anticipating human-object interaction in first person videos. Most existing methods ignore how the camera wearer interacts with the objects, or s…
Attention Distillation for Learning Video Representations
Miao Liu, Xin Chen, Yun Zhang +2
We address the challenging problem of learning motion representations using deep models for video recognition. To this end, we make use of attention modules that learn to highlight…