6 papers
Seeing the Unseen: Camouflaged Object Detection Beyond the Visible Spectrum
Avi Gupta, Trasha Gupta
Recent advances in camouflaged object detection (COD) have led to substantial progress in challenging low-visibility scenarios, with pioneering studies demonstrating notable succes…
SELECT: SELEctive Context Transfer for Class-Incremental Semantic Segmentation
Avi Gupta, Saurabh Yadav, Koteswar Rao Jerripothula +1
Class-Incremental Semantic Segmentation (CISS) is fundamentally challenged by catastrophic forgetting and background shift, where learning new concepts degrades performance on prev…
The devil in the (de)tails: an improved recovery guarantee for sparse approximation
Ben Adcock, Simone Brugiapaglia, Avi Gupta
Many functions exhibit approximate sparsity in their coefficients with respect to a given dictionary. In recent literature, sparse approximation in such a dictionary from i.i.d. po…
Listen, Look, and Learn: Learning Without Forgetting through SAM-Audio
Avi Gupta, Nilotpal Sinha, Vishnu Raj +4
Class-Incremental Learning (CIL) aims to continuously learn new classes without forgetting previously acquired knowledge. While recent CIL advances have spurred significant interes…
Universal, sample-optimal algorithms for recovery of anisotropic functions from i.i.d. samples
Ben Adcock, Avi Gupta
A key problem in approximation theory is the recovery of high-dimensional functions from samples. In many cases, the functions of interest exhibit anisotropic smoothness, and, in m…
SAMwave: Wavelet-Driven Feature Enrichment for Effective Adaptation of Segment Anything Model
Saurabh Yadav, Avi Gupta, Koteswar Rao Jerripothula
The emergence of large foundation models has propelled significant advances in various domains. The Segment Anything Model (SAM), a leading model for image segmentation, exemplifie…