activity
20182022
most citedThe AVA-Kinetics Localized Human Actions Video Dataset

84 citations · 127 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

10 papers · 1 filter

cs.CV2021

AI Choreographer: Music Conditioned 3D Dance Generation with AIST++

Ruilong Li, Shan Yang, David A. Ross +1

We present AIST++, a new multi-modal dataset of 3D dance motion and music, along with FACT, a Full-Attention Cross-modal Transformer network for generating 3D dance motion conditio…

cs.CV2020

Virtual Multi-view Fusion for 3D Semantic Segmentation

Abhijit Kundu, Xiaoqi Yin, Alireza Fathi +4

Semantic segmentation of 3D meshes is an important problem for 3D scene understanding. In this paper we revisit the classic multiview representation of 3D meshes and study several…

cs.CV202029 cited

Pillar-based Object Detection for Autonomous Driving

Yue Wang, Alireza Fathi, Abhijit Kundu +4

We present a simple and flexible object detection framework optimized for autonomous driving. Building on the observation that point clouds in this application are extremely sparse…

cs.CV202011 cited

An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds

Rui Huang, Wanyue Zhang, Abhijit Kundu +4

Detecting objects in 3D LiDAR data is a core technology for autonomous driving and other robotics applications. Although LiDAR data is acquired over time, most of the 3D object det…

cs.CV2020

Active Learning for Video Description With Cluster-Regularized Ensemble Ranking

David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross +1

Automatic video captioning aims to train models to generate text descriptions for all segments in a video, however, the most effective approaches require large amounts of manual an…

cs.CV202084 cited

The AVA-Kinetics Localized Human Actions Video Dataset

Ang Li, Meghana Thotakuri, David A. Ross +3

This paper describes the AVA-Kinetics localized human actions video dataset. The dataset is collected by annotating videos from the Kinetics-700 dataset using the AVA annotation pr…