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Zuoxun Hou

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2 papers

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AAAI Conference 2026 Conference Paper

Exploring Surround-View Fisheye Camera 3D Object Detection

Changcai Li
Wenwei Lin
Zuoxun Hou
Gang Chen
Wei Zhang
Huihui Zhou
Weishi Zheng

In this work, we explore the technical feasibility of implementing end-to-end 3D object detection (3DOD) with surround-view fisheye camera system. Specifically, we first investigate the performance drop incurred when transferring classic pinhole-based 3D object detectors to fisheye imagery. To mitigate this, we then develop two methods that incorporate the unique geometry of fisheye images into mainstream detection frameworks: one based on the bird's-eye-view (BEV) paradigm, named FisheyeBEVDet, and the other on the query-based paradigm, named FisheyePETR. Both methods adopt spherical spatial representations to effectively capture fisheye geometry. In light of the lack of dedicated evaluation benchmarks, we release Fisheye3DOD, a new open dataset synthesized using CARLA and featuring both standard pinhole and fisheye camera arrays. Experiments on Fisheye3DOD demonstrate that our fisheye-compatible modeling improves accuracy by up to 6.2% compared to baseline methods.

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AAAI Conference 2025 Conference Paper

M2Flow: A Motion Information Fusion Framework for Enhanced Unsupervised Optical Flow Estimation in Autonomous Driving

Xunpei Sun
Gang Chen
Zuoxun Hou

Estimating optical flow in occluded regions is a crucial challenge in unsupervised settings. In this work, we introduce M2Flow, a novel framework for unsupervised optical flow estimation that integrates motion information from multiple frames to address occlusions. By modeling inter-frame motion information and employing Motion Information Propagation (MIP) module, M2Flow effectively propagates and integrates motion information across frames, while concurrently estimating bidirectional optical flows for multiple frames. In addition, to handle occlusions across multiple frames, we provide two augmentation modules specifically designed for our multi-frame model to further refine optical flow. The experiments on KITTI and Sintel datasets demonstrate that M2Flow outperforms other state-of-the-art unsupervised approaches, especially in solving occlusions.

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