4 papers
Synthetic-to-Real Translation for Class-Agnostic Motion Prediction
Yizheng Wu, Hongwei Fan, Kewei Wang +8
Motion understanding is critical for ensuring safety and robustness in autonomous driving systems, driving increasing interest in motion prediction. A key challenge in this domain…
DSOcc: Leveraging Depth Awareness and Semantic Aid to Boost Camera-Based 3D Semantic Occupancy Prediction
Naiyu Fang, Zheyuan Zhou, Kang Wang +5
Camera-based 3D semantic occupancy prediction offers an efficient and cost-effective solution for perceiving surrounding scenes in autonomous driving. However, existing works rely…
Weakly and Self-Supervised Class-Agnostic Motion Prediction for Autonomous Driving
Ruibo Li, Hanyu Shi, Zhe Wang +1
Understanding motion in dynamic environments is critical for autonomous driving, thereby motivating research on class-agnostic motion prediction. In this work, we investigate weakl…
TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion
Yiran Wang, Jiaqi Li, Chaoyi Hong +6
Radar-Camera depth estimation aims to predict dense and accurate metric depth by fusing input images and Radar data. Model efficiency is crucial for this task in pursuit of real-ti…