从25年顶会论文方向看后期研究热点是怎么样的？

Core Insights - The article highlights the key research directions in computer vision and autonomous driving as presented at major conferences CVPR and ICCV, focusing on four main areas: general computer vision, autonomous driving, embodied intelligence, and 3D vision [2][3]. Group 1: Research Directions - In the field of computer vision and image processing, the main research topics include diffusion models, image quality assessment, semi-supervised learning, zero-shot learning, and open-world detection [3]. - Autonomous driving research is concentrated on end-to-end systems, closed-loop simulation, 3D ground segmentation (3DGS), multimodal large models, diffusion models, world models, and trajectory prediction [3]. - Embodied intelligence focuses on visual language navigation (VLA), zero-shot learning, robotic manipulation, end-to-end systems, sim-to-real transfer, and dexterous grasping [3]. - The 3D vision domain emphasizes point cloud completion, single-view reconstruction, 3D ground segmentation (3DGS), 3D matching, video compression, and Neural Radiance Fields (NeRF) [3]. Group 2: Research Support and Collaboration - The article offers support for various research needs in autonomous driving, including large models, VLA, end-to-end autonomous driving, 3DGS, BEV perception, target tracking, and multi-sensor fusion [4]. - In the embodied intelligence area, support is provided for VLA, visual language navigation, end-to-end systems, reinforcement learning, diffusion policy, sim-to-real, embodied interaction, and robotic decision-making [4]. - For 3D vision, the focus is on point cloud processing, 3DGS, and SLAM [4]. - General computer vision support includes diffusion models, image quality assessment, semi-supervised learning, and zero-shot learning [4].