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20172026
most citedImage to Image Translation for Domain Adaptation

25 citations · 75 across the 27 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

KG-FairDiff: Knowledge Graph-Guided Prompt Refinement for Demographically Fair Text-to-Image Generation

Farbod Davoodi, Seyed Reza Tavakoli Shiyadeh, Pooria Safaei +12

Text-to-Image (TTI) systems are now everyday infrastructure for journalism, education, advertising, and public communication, and the demographic and cultural stereotypes they inhe…

cs.CV2026

From Imitation to Intuition: Intrinsic Reasoning for Open-Instance Video Classification

Ke Zhang, Xiangchen Zhao, Yunjie Tian +3

Conventional video classification models, acting as effective imitators, excel in scenarios with homogeneous data distributions. However, real-world applications often present an o…

cs.CV2026

SurgFormer: Scalable Learning of Organ Deformation with Resection Support and Real-Time Inference

Ashkan Shahbazi, Elaheh Akbari, Kyvia Pereira +7

We introduce SurgFormer, a multiresolution gated transformer for data driven soft tissue simulation on volumetric meshes. High fidelity biomechanical solvers are often too costly f…

cs.CV2026

Vector-Quantized Soft Label Compression for Dataset Distillation

Ali Abbasi, Ashkan Shahbazi, Hamed Pirsiavash +1

Dataset distillation is an emerging technique for reducing the computational and storage costs of training machine learning models by synthesizing a small, informative subset of da…

cs.CV2025

Efficient Transferable Optimal Transport via Min-Sliced Transport Plans

Xinran Liu, Elaheh Akbari, Rocio Diaz Martin +2

Optimal Transport (OT) offers a powerful framework for finding correspondences between distributions and addressing matching and alignment problems in various areas of computer vis…

cs.CV2024

Diffusion-Augmented Coreset Expansion for Scalable Dataset Distillation

Ali Abbasi, Shima Imani, Chenyang An +6

With the rapid scaling of neural networks, data storage and communication demands have intensified. Dataset distillation has emerged as a promising solution, condensing information…