6 papers
Music Audio-Visual Question Answering Requires Specialized Multimodal Designs
Wenhao You, Xingjian Diao, Wenjun Huang +9
While recent Multimodal Large Language Models exhibit impressive capabilities for general multimodal tasks, specialized domains like music necessitate tailored approaches. Music Au…
ProtoVQA: An Adaptable Prototypical Framework for Explainable Fine-Grained Visual Question Answering
Xingjian Diao, Weiyi Wu, Keyi Kong +5
Visual Question Answering (VQA) is increasingly used in diverse applications ranging from general visual reasoning to safety-critical domains such as medical imaging and autonomous…
Learning Sparsity for Effective and Efficient Music Performance Question Answering
Xingjian Diao, Tianzhen Yang, Chunhui Zhang +3
Music performances, characterized by dense and continuous audio as well as seamless audio-visual integration, present unique challenges for multimodal scene understanding and reaso…
Learning Musical Representations for Music Performance Question Answering
Xingjian Diao, Chunhui Zhang, Tingxuan Wu +4
Music performances are representative scenarios for audio-visual modeling. Unlike common scenarios with sparse audio, music performances continuously involve dense audio signals th…
Temporal Working Memory: Query-Guided Segment Refinement for Enhanced Multimodal Understanding
Xingjian Diao, Chunhui Zhang, Weiyi Wu +5
Multimodal foundation models (MFMs) have demonstrated significant success in tasks such as visual captioning, question answering, and image-text retrieval. However, these models fa…
FT2TF: First-Person Statement Text-To-Talking Face Generation
Xingjian Diao, Ming Cheng, Wayner Barrios +1
Talking face generation has gained immense popularity in the computer vision community, with various applications including AR, VR, teleconferencing, digital assistants, and avatar…