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cs.CV2026

Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving

Linbo Wang, Yupeng Zheng, Qiang Chen +13

We introduce Latent-WAM, an efficient end-to-end autonomous driving framework that achieves strong trajectory planning through spatially-aware and dynamics-informed latent world re…

cs.CV2026

Enhancing Indoor Occupancy Prediction via Sparse Query-Based Multi-Level Consistent Knowledge Distillation

Xiang Li, Yupeng Zheng, Pengfei Li +3

Occupancy prediction provides critical geometric and semantic understanding for robotics but faces efficiency-accuracy trade-offs. Current dense methods suffer computational waste…

cs.CV2025

Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving

Xiang Li, Pengfei Li, Yupeng Zheng +3

Understanding world dynamics is crucial for planning in autonomous driving. Recent methods attempt to achieve this by learning a 3D occupancy world model that forecasts future surr…

cs.CV2024

HiPrompt: Tuning-free Higher-Resolution Generation with Hierarchical MLLM Prompts

Xinyu Liu, Yingqing He, Lanqing Guo +10

The potential for higher-resolution image generation using pretrained diffusion models is immense, yet these models often struggle with issues of object repetition and structural a…

cs.CV2024

MonoOcc: Digging into Monocular Semantic Occupancy Prediction

Yupeng Zheng, Xiang Li, Pengfei Li +6

Monocular Semantic Occupancy Prediction aims to infer the complete 3D geometry and semantic information of scenes from only 2D images. It has garnered significant attention, partic…