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20242026
most citedDatUS^2: Data-driven Unsupervised Semantic Segmentation with Pre-trained Self-supervised Vision Transformer

6 citations · 7 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer

Alik Pramanick, Utsav Bheda, Arijit Sur

Recently, transformers have captured significant interest in the area of single-image super-resolution tasks, demonstrating substantial gains in performance. Current models heavily…

cs.CV2024

Harnessing Multi-resolution and Multi-scale Attention for Underwater Image Restoration

Alik Pramanick, Arijit Sur, V. Vijaya Saradhi

Underwater imagery is often compromised by factors such as color distortion and low contrast, posing challenges for high-level vision tasks. Recent underwater image restoration (UI…

cs.CV2024

Zero-Shot Underwater Gesture Recognition

Sandipan Sarma, Gundameedi Sai Ram Mohan, Hariansh Sehgal +1

Hand gesture recognition allows humans to interact with machines non-verbally, which has a huge application in underwater exploration using autonomous underwater vehicles. Recently…

eess.IV2024★ 1 cited

Segmentation of tibiofemoral joint tissues from knee MRI using MtRA-Unet and incorporating shape information: Data from the Osteoarthritis Initiative

Akshay Daydar, Alik Pramanick, Arijit Sur +1

Knee Osteoarthritis (KOA) is the third most prevalent Musculoskeletal Disorder (MSD) after neck and back pain. To monitor such a severe MSD, a segmentation map of the femur, tibia…

cs.CV2024★ 6 cited

DatUS^2: Data-driven Unsupervised Semantic Segmentation with Pre-trained Self-supervised Vision Transformer

Sonal Kumar, Arijit Sur, Rashmi Dutta Baruah

Successive proposals of several self-supervised training schemes continue to emerge, taking one step closer to developing a universal foundation model. In this process, the unsuper…