Vision Task
Vision tasks, encompassing image and video analysis for diverse applications, are a central focus in computer vision research. Current efforts concentrate on improving model efficiency and robustness, particularly through multi-task learning, the development of novel architectures like Vision Transformers and state-space models, and the incorporation of human feedback for improved alignment with user preferences. These advancements are driving progress in areas such as image compression for machine learning pipelines, multi-image understanding, and the creation of more robust and fair models for real-world deployment.
Papers
YOLOv11: An Overview of the Key Architectural Enhancements
Rahima Khanam, Muhammad Hussain
MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models
Ziyu Liu, Yuhang Zang, Xiaoyi Dong, Pan Zhang, Yuhang Cao, Haodong Duan, Conghui He, Yuanjun Xiong, Dahua Lin, Jiaqi Wang