activity
20182022
most citedWhat to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactions

1 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

What to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactions

A S M Iftekhar, Hao Chen, Kaustav Kundu +3

We propose a novel one-stage Transformer-based semantic and spatial refined transformer (SSRT) to solve the Human-Object Interaction detection task, which requires to localize huma…

cs.CV20221 cited

Hierarchical Self-supervised Representation Learning for Movie Understanding

Fanyi Xiao, Kaustav Kundu, Joseph Tighe +1

Most self-supervised video representation learning approaches focus on action recognition. In contrast, in this paper we focus on self-supervised video learning for movie understan…

cs.CV2020

Positive-Congruent Training: Towards Regression-Free Model Updates

Sijie Yan, Yuanjun Xiong, Kaustav Kundu +5

Reducing inconsistencies in the behavior of different versions of an AI system can be as important in practice as reducing its overall error. In image classification, sample-wise i…

cs.CV2018

SurfConv: Bridging 3D and 2D Convolution for RGBD Images

Hang Chu, Wei-Chiu Ma, Kaustav Kundu +2

We tackle the problem of using 3D information in convolutional neural networks for down-stream recognition tasks. Using depth as an additional channel alongside the RGB input has t…

cs.CV2018

Pose Estimation for Objects with Rotational Symmetry

Enric Corona, Kaustav Kundu, Sanja Fidler

Pose estimation is a widely explored problem, enabling many robotic tasks such as grasping and manipulation. In this paper, we tackle the problem of pose estimation for objects tha…