activity
20242026
collaborators

9 papers

cs.CV2026

MotionHint: Self-Supervised Monocular Visual Odometry with Motion Constraints

Cong Wang, Yu-Ping Wang, Dinesh Manocha

We present a novel self-supervised algorithm named MotionHint for monocular visual odometry (VO) that takes motion constraints into account. A key aspect of our approach is to use…

cs.RO2025

Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation

Bhrij Patel, Kasun Weerakoon, Wesley A. Suttle +5

Reinforcement learning (RL) is a promising approach for robotic navigation, allowing robots to learn through trial and error. However, real-world robotic tasks often suffer from sp…

cs.CV2024

Show Me What I Like: Detecting User-Specific Video Highlights Using Content-Based Multi-Head Attention

Uttaran Bhattacharya, Gang Wu, Stefano Petrangeli +2

We propose a method to detect individualized highlights for users on given target videos based on their preferred highlight clips marked on previous videos they have watched. Our m…

cs.CV2024

HighlightMe: Detecting Highlights from Human-Centric Videos

Uttaran Bhattacharya, Gang Wu, Stefano Petrangeli +2

We present a domain- and user-preference-agnostic approach to detect highlightable excerpts from human-centric videos. Our method works on the graph-based representation of multipl…

cs.MM2024

Speech2AffectiveGestures: Synthesizing Co-Speech Gestures with Generative Adversarial Affective Expression Learning

Uttaran Bhattacharya, Elizabeth Childs, Nicholas Rewkowski +1

We present a generative adversarial network to synthesize 3D pose sequences of co-speech upper-body gestures with appropriate affective expressions. Our network consists of two com…

cs.HC2024

Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents

Uttaran Bhattacharya, Nicholas Rewkowski, Abhishek Banerjee +3

We present Text2Gestures, a transformer-based learning method to interactively generate emotive full-body gestures for virtual agents aligned with natural language text inputs. Our…