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cs.CV2026

Seek to Segment: Active Perception for Panoramic Referring Segmentation

Song Tang, Shuming Hu, Xincheng Shuai +2

Existing referring segmentation models passively process static images captured from fixed perspectives, limiting their applicability in Embodied AI, where agents must perform acti…

cs.CV2026

AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs

Yaoting Wang, Ziyi Zhang, Wenming Tu +10

Recent advances in Omni-Multimodal Large Language Models (Omni-MLLMs) have enabled strong integration of vision, audio, and language. However, their audio-visual intelligence (AVI)…

cs.CV2026

ROSE: Retrieval-Oriented Segmentation Enhancement

Song Tang, Guangquan Jie, Henghui Ding +1

Existing segmentation models based on multimodal large language models (MLLMs), such as LISA, often struggle with novel or emerging entities due to their inability to incorporate u…

cs.CV2026

PSDesigner: Automated Graphic Design with a Human-Like Creative Workflow

Xincheng Shuai, Song Tang, Yutong Huang +2

Graphic design is a creative and innovative process that plays a crucial role in applications such as e-commerce and advertising. However, developing an automated design system tha…

cs.CV2026

GlyphPrinter: Region-Grouped Direct Preference Optimization for Glyph-Accurate Visual Text Rendering

Xincheng Shuai, Ziye Li, Henghui Ding +1

Generating accurate glyphs for visual text rendering is essential yet challenging. Existing methods typically enhance text rendering by training on a large amount of high-quality s…

cs.CV2026

Audit After Segmentation: Reference-Free Mask Quality Assessment for Language-Referred Audio-Visual Segmentation

Jinxing Zhou, Yanghao Zhou, Yaoting Wang +5

Language-referred audio-visual segmentation (Ref-AVS) aims to segment target objects described by natural language by jointly reasoning over video, audio, and text. Beyond generati…