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20162023
most citedCOVID-Robot: Monitoring Social Distancing Constraints in Crowded Scenarios

55 citations · 256 across the 65 of their papers we have counts for

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24 papers · 1 filter

cs.CV2023

AdVerb: Visually Guided Audio Dereverberation

Sanjoy Chowdhury, Sreyan Ghosh, Subhrajyoti Dasgupta +3

We present AdVerb, a novel audio-visual dereverberation framework that uses visual cues in addition to the reverberant sound to estimate clean audio. Although audio-only dereverber…

cs.CV2023

Human Trajectory Forecasting with Explainable Behavioral Uncertainty

Jiangbei Yue, Dinesh Manocha, He Wang

Human trajectory forecasting helps to understand and predict human behaviors, enabling applications from social robots to self-driving cars, and therefore has been heavily investig…

cs.CV20225 cited

STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes

Peishan Cong, Xinge Zhu, Feng Qiao +7

Accurately detecting and tracking pedestrians in 3D space is challenging due to large variations in rotations, poses and scales. The situation becomes even worse for dense crowds w…

cs.CV20221 cited

3MASSIV: Multilingual, Multimodal and Multi-Aspect dataset of Social Media Short Videos

Vikram Gupta, Trisha Mittal, Puneet Mathur +5

We present 3MASSIV, a multilingual, multimodal and multi-aspect, expertly-annotated dataset of diverse short videos extracted from short-video social media platform - Moj. 3MASSIV…

cs.CV2022

SelfTune: Metrically Scaled Monocular Depth Estimation through Self-Supervised Learning

Jaehoon Choi, Dongki Jung, Yonghan Lee +3

Monocular depth estimation in the wild inherently predicts depth up to an unknown scale. To resolve scale ambiguity issue, we present a learning algorithm that leverages monocular…

cs.CV2021

Active Learning of Neural Collision Handler for Complex 3D Mesh Deformations

Qingyang Tan, Zherong Pan, Breannan Smith +2

We present a robust learning algorithm to detect and handle collisions in 3D deforming meshes. Our collision detector is represented as a bilevel deep autoencoder with an attention…