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cs.CV2025

Realistic and Controllable 3D Gaussian-Guided Object Editing for Driving Video Generation

Jiusi Li, Jackson Jiang, Jinyu Miao +10

Corner cases are crucial for training and validating autonomous driving systems, yet collecting them from the real world is often costly and hazardous. Editing objects within captu…

cs.CV2025

EFFOcc: Learning Efficient Occupancy Networks from Minimal Labels for Autonomous Driving

Yining Shi, Kun Jiang, Jinyu Miao +8

3D occupancy prediction (3DOcc) is a rapidly rising and challenging perception task in the field of autonomous driving. Existing 3D occupancy networks (OccNets) are both computatio…

cs.CV2024

PanoSSC: Exploring Monocular Panoptic 3D Scene Reconstruction for Autonomous Driving

Yining Shi, Jiusi Li, Kun Jiang +4

Vision-centric occupancy networks, which represent the surrounding environment with uniform voxels with semantics, have become a new trend for safe driving of camera-only autonomou…

cs.CV2024

StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation

Yining Shi, Kun Jiang, Ke Wang +4

Predicting the future occupancy states of the surrounding environment is a vital task for autonomous driving. However, current best-performing single-modality methods or multi-moda…

cs.CV2024

Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review

Yining Shi, Kun Jiang, Jiusi Li +5

Grid-centric perception is a crucial field for mobile robot perception and navigation. Nonetheless, grid-centric perception is less prevalent than object-centric perception as auto…