2 papers
cs.CV2026
Not Just What's There: Enabling CLIP to Comprehend Negated Visual Descriptions Without Fine-tuning
Junhao Xiao, Zhiyu Wu, Hao Lin +5
Vision-Language Models (VLMs) like CLIP struggle to understand negation, often embedding affirmatives and negatives similarly (e.g., matching "no dog" with dog images). Existing me…
cs.CV2024
LTOS: Layout-controllable Text-Object Synthesis via Adaptive Cross-attention Fusions
Xiaoran Zhao, Tianhao Wu, Yu Lai +5
Controllable text-to-image generation synthesizes visual text and objects in images with certain conditions, which are frequently applied to emoji and poster generation. Visual tex…