3 accepted papers
Understanding human intents from multimodal signals is critical for analyzing human behaviors and enhancing human-machine interactions in real-world scenarios. However, existing methods exhibit limitations in their modality-level reliance, constraining relational reasoning over fine-grained semantic
Reasoning stands as a cornerstone of intelligence, enabling the synthesis of existing knowledge to solve complex problems. Despite remarkable progress, existing reasoning benchmarks often fail to rigorously evaluate the nuanced reasoning capabilities required for complex, real-world problemsolving,…
Generating virtual object shadows consistent with the real-world environment shading effects is important but challenging in computer vision and augmented reality applications. To address this problem, we propose an end-to-end Generative Adversarial Network for shadow generation named ARShadowGAN fo…