1 citations · 1 across the 7 of their papers we have counts for
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Rethinking Prompting Strategies for Multi-Label Recognition with Partial Annotations
Samyak Rawlekar, Shubhang Bhatnagar, Narendra Ahuja
Vision-language models (VLMs) like CLIP have been adapted for Multi-Label Recognition (MLR) with partial annotations by leveraging prompt-learning, where positive and negative prom…
Potential Field Based Deep Metric Learning
Shubhang Bhatnagar, Narendra Ahuja
Deep metric learning (DML) involves training a network to learn a semantically meaningful representation space. Many current approaches mine n-tuples of examples and model interact…
Improving Multi-label Recognition using Class Co-Occurrence Probabilities
Samyak Rawlekar, Shubhang Bhatnagar, Vishnuvardhan Pogunulu Srinivasulu +1
Multi-label Recognition (MLR) involves the identification of multiple objects within an image. To address the additional complexity of this problem, recent works have leveraged inf…
Piecewise-Linear Manifolds for Deep Metric Learning
Shubhang Bhatnagar, Narendra Ahuja
Unsupervised deep metric learning (UDML) focuses on learning a semantic representation space using only unlabeled data. This challenging problem requires accurately estimating the…