most citedESA: Annotation-Efficient Active Learning for Semantic Segmentation

5 citations · 8 across the 4 of their papers we have counts for

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cs.CV2025

UniVid: The Open-Source Unified Video Model

Jiabin Luo, Junhui Lin, Zeyu Zhang +4

Unified video modeling that combines generation and understanding capabilities is increasingly important but faces two key challenges: maintaining semantic faithfulness during flow…

cs.CV2025

VaseVQA: Multimodal Agent and Benchmark for Ancient Greek Pottery

Jinchao Ge, Tengfei Cheng, Biao Wu +7

Understanding cultural heritage artifacts such as ancient Greek pottery requires expert-level reasoning that remains challenging for current MLLMs due to limited domain-specific da…

cs.CV2025

PresentAgent: Multimodal Agent for Presentation Video Generation

Jingwei Shi, Zeyu Zhang, Biao Wu +4

We present PresentAgent, a multimodal agent that transforms long-form documents into narrated presentation videos. While existing approaches are limited to generating static slides…

cs.CV2024★ 5 cited

ESA: Annotation-Efficient Active Learning for Semantic Segmentation

Jinchao Ge, Zeyu Zhang, Minh Hieu Phan +4

Active learning enhances annotation efficiency by selecting the most revealing samples for labeling, thereby reducing reliance on extensive human input. Previous methods in semanti…

cs.CV2024★ 3 cited

MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training

Biao Wu, Yutong Xie, Zeyu Zhang +4

Vision-and-language pretraining (VLP) in the medical field utilizes contrastive learning on image-text pairs to achieve effective transfer across tasks. Yet, current VLP approaches…