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20132026
most citedDeep Learning for Unsupervised Anomaly Localization in Industrial Images: A Survey

216 citations · 360 across the 30 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.CV2026

From Visual Feedback to Textual Reviews: A Multi-Agent Vision-Language Framework for Image-Grounded Review Assistance

Utsav Kumar Nareti, Ayush Bansal, Kumari Priya +4

Visual feedback in the form of user-uploaded images and videos is becoming increasingly common in e-commerce platforms because it provides authentic evidence of product quality, de…

cs.CV2026

From Visual Attribution to Clinical Reasoning: Explainable Parkinson's Disease Screening from Hand-Drawn Patterns

Aritra Dey, Utsav Kumar Nareti, Chandranath Adak +3

Parkinson's disease (PD) manifests early neuromotor impairments that become observable in controlled hand-drawn patterns such as spirals and meanders, where tremor-induced oscillat…

cs.MM2026

Modality Agreement- and Conflict-Aware Prototype Hypergraph Learning for Multimodal Intent Understanding

Mohnish Raj, Suraj Kumar, Soumi Chattopadhayay +2

Multimodal intent recognition requires understanding not only what textual, acoustic, and visual signals share, but also how they disagree. Such disagreement is frequently class-in…

cs.MM2026

Adaptive Modality Reliability Diagnosis and Restoration for Robust Multimodal Intent Recognition

Suraj Kumar, Mohnish Raj, Soumi Chattopadhayay +2

Multimodal intent recognition combines linguistic, acoustic, and visual evidence, but individual modalities may be noisy, missing, semantically conflicting, or disproportionately d…

cs.AI2026

Deep Learning-Based Sign Language Recognition from Videos and Cross-Lingual Translation to Indian Vernaculars

Ramesh Nandipalli, Chandranath Adak

Sign language is a primary mode of communication for the global deaf and hard-of-hearing community, yet automated tools that recognize sign gestures from video and translate them i…

cs.AI2026

SAiW: Source-Attributable Invisible Watermarking for Proactive Deepfake Defense

Bibek Das, Chandranath Adak, Soumi Chattopadhyay +2

Deepfakes generated by modern generative models pose a serious threat to information integrity, digital identity, and public trust. Existing detection methods are largely reactive,…