3 citations · 4 across the 8 of their papers we have counts for
7 papers · 1 filter
Mitigating Saliency Collapse: Robust Saliency-Aware Long-Text Image-Text Alignment
Qiuyu Kong, Zanxi Ruan, Marco Cristani +1
Long-text image-text alignment is essential for fine-grained scene understanding, yet existing methods mainly focus on extending context length or improving local alignment. We ide…
Is SAM3 ready for pathology segmentation?
Qiuyu Kong, Shakiba Sharifi, Yiming Wang +2
Is Segment Anything Model 3 (SAM3) capable in segmenting Any Pathology Images? Digital pathology segmentation spans tissue-level and nuclei-level scales, where traditional methods…
Anomaly-Aware Vision-Language Adapters for Zero-Shot Anomaly Detection
Muhammad Aqeel, Maham Nazir, Uzair Khan +2
Zero-shot anomaly detection aims to identify defects in unseen categories without target-specific training. Existing methods usually apply the same feature transformation to all sa…
Benchmarking Interaction, Beyond Policy: a Reproducible Benchmark for Collaborative Instance Object Navigation
Edoardo Zorzi, Francesco Taioli, Yiming Wang +4
We propose Question-Asking Navigation (QAsk-Nav), the first reproducible benchmark for Collaborative Instance Object Navigation (CoIN) that enables an explicit, separate assessment…
StructXLIP: Enhancing Vision-language Models with Multimodal Structural Cues
Zanxi Ruan, Songqun Gao, Qiuyu Kong +2
Edge-based representations are fundamental cues for visual understanding, a principle rooted in early vision research and still central today. We extend this principle to vision-la…
Multi-Level Conditioning by Pairing Localized Text and Sketch for Fashion Image Generation
Ziyue Liu, Davide Talon, Federico Girella +5
Sketches offer designers a concise yet expressive medium for early-stage fashion ideation by specifying structure, silhouette, and spatial relationships, while textual descriptions…
VISOR: VIsual Spatial Object Reasoning for Language-driven Object Navigation
Francesco Taioli, Shiping Yang, Sonia Raychaudhuri +3
Language-driven object navigation requires agents to interpret natural language descriptions of target objects, which combine intrinsic and extrinsic attributes for instance recogn…