5 citations · 12 across the 11 of their papers we have counts for
12 papers
ReGain: Restoring Subject Fidelity in Personalization on Synthetic Images
Shubhang Bhatnagar, Ishan Bhatnagar, Viraj Shah +1
Text-to-image diffusion models are personalized to a subject by DreamBooth fine-tuning on a handful of its images. Increasingly, these images come from a diffusion model rather tha…
Beyond Scalar Distances: Semantic Attribute Gradients from Frozen MLLMs for Visual Embeddings
Shubhang Bhatnagar, Dheeraj Baiju, Narendra Ahuja
Vision encoders for retrieval are typically trained with class-label supervision: each training pair reduces to a scalar that uniformly pushes the embedding apart or pulls it toget…
LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models
Shubhang Bhatnagar, Andy Xu, Kar-Han Tan +1
Large Language Models (LLMs) with multimodal capabilities have revolutionized vision-language tasks, but their deployment often requires huge memory and computational resources. Po…
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…
Long-Distance Gesture Recognition using Dynamic Neural Networks
Shubhang Bhatnagar, Sharath Gopal, Narendra Ahuja +1
Gestures form an important medium of communication between humans and machines. An overwhelming majority of existing gesture recognition methods are tailored to a scenario where hu…
Memory Efficient Adaptive Attention For Multiple Domain Learning
Himanshu Pradeep Aswani, Abhiraj Sunil Kanse, Shubhang Bhatnagar +1
Training CNNs from scratch on new domains typically demands large numbers of labeled images and computations, which is not suitable for low-power hardware. One way to reduce these…
Analyzing Cross Validation In Compressed Sensing With Mixed Gaussian And Impulse Measurement Noise With L1 Errors
Chinmay Gurjarpadhye, Shubhang Bhatnagar, Ajit Rajwade
Compressed sensing (CS) involves sampling signals at rates less than their Nyquist rates and attempting to reconstruct them after sample acquisition. Most such algorithms have para…
PAL : Pretext-based Active Learning
Shubhang Bhatnagar, Sachin Goyal, Darshan Tank +1
The goal of pool-based active learning is to judiciously select a fixed-sized subset of unlabeled samples from a pool to query an oracle for their labels, in order to maximize the…
QR code denoising using parallel Hopfield networks
Ishan Bhatnagar, Shubhang Bhatnagar
We propose a novel algorithm for using Hopfield networks to denoise QR codes. Hopfield networks have mostly been used as a noise tolerant memory or to solve difficult combinatorial…