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20242026
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cs.CV2026

Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development

Zhongying Deng, Cheng Tang, Ziyan Huang +124

Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…

cs.CV2025

UniPercept: Towards Unified Perceptual-Level Image Understanding across Aesthetics, Quality, Structure, and Texture

Shuo Cao, Jiayang Li, Xiaohui Li +12

Multimodal large language models (MLLMs) have achieved remarkable progress in visual understanding tasks such as visual grounding, segmentation, and captioning. However, their abil…

cs.CV2025

LayerT2V: A Unified Multi-Layer Video Generation Framework

Guangzhao Li, Kangrui Cen, Baixuan Zhao +5

Text-to-video generation has advanced rapidly, but existing methods typically output only the final composited video and lack editable layered representations, limiting their use i…

cs.CV2025

TR-PTS: Task-Relevant Parameter and Token Selection for Efficient Tuning

Siqi Luo, Haoran Yang, Yi Xin +4

Large pre-trained models achieve remarkable performance in vision tasks but are impractical for fine-tuning due to high computational and storage costs. Parameter-Efficient Fine-Tu…

cs.CV2025

Resurrect Mask AutoRegressive Modeling for Efficient and Scalable Image Generation

Yi Xin, Le Zhuo, Qi Qin +8

AutoRegressive (AR) models have made notable progress in image generation, with Masked AutoRegressive (MAR) models gaining attention for their efficient parallel decoding. However,…

cs.CV2024

Enhancing Test Time Adaptation with Few-shot Guidance

Siqi Luo, Yi Xin, Yuntao Du +3

Deep neural networks often encounter significant performance drops while facing with domain shifts between training (source) and test (target) data. To address this issue, Test Tim…