MIM4D: How Self-Supervised 4D Learning Revolutionizes Autonomous Driving Perception
2 days ago 高效码农MIM4D: Masked Multi-View Video Modeling for Autonomous Driving Representation Learning Why Autonomous Driving Needs Better Visual Representation Learning? In autonomous driving systems, multi-view video data captured by cameras forms the backbone of environmental perception. However, current approaches face two critical challenges: Dependency on Expensive 3D Annotations: Traditional supervised learning requires massive labeled 3D datasets, limiting scalability. Ignored Temporal Dynamics: Single-frame or monocular methods fail to capture motion patterns in dynamic scenes. MIM4D (Masked Modeling with Multi-View Video for Autonomous Driving) introduces an innovative solution. Through dual-path masked modeling (spatial + temporal) and 3D volumetric rendering, it learns robust geometric representations …
Web-SSL: Scaling Visual Representation Learning Beyond Language Supervision
1 months ago 高效码农Web-SSL: Redefining Visual Representation Learning Without Language Supervision The Shift from Language-Dependent to Vision-Only Models In the realm of computer vision, language-supervised models like CLIP have long dominated multimodal research. However, the Web-SSL model family, developed through a collaboration between Meta and leading universities, achieves groundbreaking results using purely visual self-supervised learning (SSL). This research demonstrates that large-scale vision-only training can not only match traditional vision task performance but also surpass language-supervised models in text-rich scenarios like OCR and chart understanding. This article explores Web-SSL’s technical innovations and provides actionable implementation guidelines. Key Breakthroughs: Three Pillars of Visual SSL 1. …