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20242026
most citedGen-SIS: Generative Self-augmentation Improves Self-supervised Learning

2 citations · 4 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

Pathologist Attention-Aligned Report Generation for Prostate Histopathology

Ruoyu Xue, Suryakant Singh, Souradeep Chakraborty +12

The allocation of visual attention by pathologists during cancer diagnosis is a highly selective process that critically shapes the information extracted from whole-slide images (W…

cs.CV2026

Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generation

Suryakant Singh, Saarthak Kapse, Joel Saltz +1

Whole-slide pathology report generation requires models to integrate localized histomorphology, global tissue context, and diagnostically relevant semantic information, yet existin…

cs.CV2025

TICON: A Slide-Level Tile Contextualizer for Histopathology Representation Learning

Varun Belagali, Saarthak Kapse, Pierre Marza +12

The interpretation of small tiles in large whole slide images (WSI) often needs a larger image context. We introduce TICON, a transformer-based tile representation contextualizer t…

cs.CV2025

CDG-MAE: Cross-view Masked Modeling using Diffusion Generated Views

Varun Belagali, Pierre Marza, Srikar Yellapragada +7

Cross-view masked autoencoding has emerged as a powerful pretext task for learning dense correspondences, which are essential for applications such as video label propagation. The…

cs.CV2025

GECKO: Gigapixel Vision-Concept Contrastive Pretraining in Histopathology

Saarthak Kapse, Pushpak Pati, Srikar Yellapragada +5

Pretraining a Multiple Instance Learning (MIL) aggregator enables the derivation of Whole Slide Image (WSI)-level embeddings from patch-level representations without supervision. W…

cs.CV2024★ 2 cited

Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning

Varun Belagali, Srikar Yellapragada, Alexandros Graikos +7

Self-supervised learning (SSL) methods have emerged as strong visual representation learners by training an image encoder to maximize similarity between features of different views…

cs.CV2024★ 1 cited

ZoomLDM: Latent Diffusion Model for multi-scale image generation

Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis +4

Diffusion models have revolutionized image generation, yet several challenges restrict their application to large-image domains, such as digital pathology and satellite imagery. Gi…