activity
20182021
most citedContext-Aware Query Selection for Active Learning in Event Recognition

21 citations · 30 across the 4 of their papers we have counts for

collaborators

10 papers

cs.LG2021

Unsupervised Multi-source Domain Adaptation Without Access to Source Data

Sk Miraj Ahmed, Dripta S. Raychaudhuri, Sujoy Paul +2

Unsupervised Domain Adaptation (UDA) aims to learn a predictor model for an unlabeled domain by transferring knowledge from a separate labeled source domain. However, most of these…

cs.CV2020

Adversarial Knowledge Transfer from Unlabeled Data

Akash Gupta, Rameswar Panda, Sujoy Paul +2

While machine learning approaches to visual recognition offer great promise, most of the existing methods rely heavily on the availability of large quantities of labeled training d…

cs.CV2020

Domain Adaptive Semantic Segmentation Using Weak Labels

Sujoy Paul, Yi-Hsuan Tsai, Samuel Schulter +2

Learning semantic segmentation models requires a huge amount of pixel-wise labeling. However, labeled data may only be available abundantly in a domain different from the desired t…

cs.LG20199 cited

Learning from Trajectories via Subgoal Discovery

Sujoy Paul, Jeroen van Baar, Amit K. Roy-Chowdhury

Learning to solve complex goal-oriented tasks with sparse terminal-only rewards often requires an enormous number of samples. In such cases, using a set of expert trajectories coul…

cs.CV201921 cited

Context-Aware Query Selection for Active Learning in Event Recognition

Mahmudul Hasan, Sujoy Paul, Anastasios I. Mourikis +1

Activity recognition is a challenging problem with many practical applications. In addition to the visual features, recent approaches have benefited from the use of context, e.g.,…

cs.CV2019

Weakly Supervised Video Moment Retrieval From Text Queries

Niluthpol Chowdhury Mithun, Sujoy Paul, Amit K. Roy-Chowdhury

There have been a few recent methods proposed in text to video moment retrieval using natural language queries, but requiring full supervision during training. However, acquiring a…