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20242026
most citedA Simple Image Segmentation Framework via In-Context Examples

2 citations · 2 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality

Zekai Luo, Zongze Du, Zhouhang Zhu +7

Video face swapping is crucial in film and entertainment production, where achieving high fidelity and temporal consistency over long and complex video sequences remains a signific…

cs.CV2025

Unified Open-World Segmentation with Multi-Modal Prompts

Yang Liu, Yufei Yin, Chenchen Jing +7

In this work, we present COSINE, a unified open-world segmentation model that consolidates open-vocabulary segmentation and in-context segmentation with multi-modal prompts (e.g.,…

cs.CV2025

Learning by Imagining: Debiased Feature Augmentation for Compositional Zero-Shot Learning

Haozhe Zhang, Chenchen Jing, Mingyu Liu +2

Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object compositions by learning prior knowledge of seen primitives, \textit{i.e.}, attributes and objects…

cs.CL2025

Time Is a Feature: Exploiting Temporal Dynamics in Diffusion Language Models

Wen Wang, Bozhen Fang, Chenchen Jing +6

Diffusion large language models (dLLMs) generate text through iterative denoising, yet current decoding strategies discard rich intermediate predictions in favor of the final outpu…

cs.CV2025

PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training

Cong Chen, Mingyu Liu, Chenchen Jing +5

This paper aims to address the challenge of hallucinations in Multimodal Large Language Models (MLLMs) particularly for dense image captioning tasks. To tackle the challenge, we id…