49 citations · 100 across the 9 of their papers we have counts for
10 papers
Plan, Watch, Recover: A Benchmark and Architectures for Proactive Procedural Assistance
Kaustav Kundu, Ritvik Shrivastava, Maxim Arap +14
Proactive multimodal assistants must decide when guidance is needed and what to say, while tracking progress through extended procedures and helping users recover when they depart…
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…
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…
TubeR: Tubelet Transformer for Video Action Detection
Jiaojiao Zhao, Yanyi Zhang, Xinyu Li +10
We propose TubeR: a simple solution for spatio-temporal video action detection. Different from existing methods that depend on either an off-line actor detector or hand-designed ac…
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…
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…
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…
Annotating Object Instances with a Polygon-RNN
Lluis Castrejon, Kaustav Kundu, Raquel Urtasun +1
We propose an approach for semi-automatic annotation of object instances. While most current methods treat object segmentation as a pixel-labeling problem, we here cast it as a pol…
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection
Xiaozhi Chen, Kaustav Kundu, Yukun Zhu +3
The goal of this paper is to perform 3D object detection in the context of autonomous driving. Our method first aims at generating a set of high-quality 3D object proposals by expl…
Exploiting Semantic Information and Deep Matching for Optical Flow
Min Bai, Wenjie Luo, Kaustav Kundu +1
We tackle the problem of estimating optical flow from a monocular camera in the context of autonomous driving. We build on the observation that the scene is typically composed of a…