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cs.CV2026
Drive-HWM: Hierarchical World Models for Dynamic-Latent Guided Autonomous Driving
Zhaoxin Fan, Tianbao Zhang, Wenjun Wu +5
World models offer a promising paradigm for autonomous driving by predicting how traffic scenes may evolve and using such predictions to support action generation. However, existin…
cs.CV2025
EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers
Daiheng Gao, Shilin Lu, Shaw Walters +8
Removing unwanted concepts from large-scale text-to-image (T2I) diffusion models while maintaining their overall generative quality remains an open challenge. This difficulty is es…
cs.CV2024
MambaVO: Deep Visual Odometry Based on Sequential Matching Refinement and Training Smoothing
Shuo Wang, Wanting Li, Yongcai Wang +5
Deep visual odometry has demonstrated great advancements by learning-to-optimize technology. This approach heavily relies on the visual matching across frames. However, ambiguous m…