ALOcc: Adaptive Lifting-Based 3D Semantic Occupancy and Cost Volume-Based Flow Predictions
Chen, Dubing Fang, Jin Han, Wencheng Cheng, Xinjing Yin, Junbo Xu, Chenzhong Khan, Fahad Shahbaz Shen, Jianbing
Chen, Dubing
Fang, Jin
Han, Wencheng
Cheng, Xinjing
Yin, Junbo
Xu, Chenzhong
Khan, Fahad Shahbaz
Shen, Jianbing
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Department
Computer Vision
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Conference proceeding
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Abstract
3D semantic occupancy and flow prediction are fundamental to spatiotemporal scene understanding. This paper proposes a vision-based framework with three targeted improvements. First, we introduce an occlusion-aware adaptive lifting mechanism incorporating depth denoising. This enhances the robustness of 2D-to-3D feature transformation while mitigating reliance on depth priors. Second, we enforce 3D-2D semantic consistency via jointly optimized prototypes, using confidence- and category-aware sampling to address the long-tail classes problem. Third, to streamline joint prediction, we devise a BEV-centric cost volume to explicitly correlate semantic and flow features, supervised by a hybrid classification-regression scheme that handles diverse motion scales. Our purely convolutional architecture establishes new SOTA performance on multiple benchmarks for both semantic occupancy and joint occupancy semantic-flow prediction. We also present a family of models offering a spectrum of efficiency-performance trade-offs. Our real-time version exceeds all existing real-time methods in speed and accuracy, ensuring its practical viability.
Citation
D. Chen, J. Fang, W. Han, X. Cheng, J. Yin, C. Xu , et al., "ALOcc: Adaptive Lifting-Based 3D Semantic Occupancy and Cost Volume-Based Flow Predictions," 2026, pp. 4156-4166.
Source
2025 IEEE/CVF International Conference on Computer Vision (ICCV)
Conference
2025 IEEE/CVF International Conference on Computer Vision (ICCV)
Keywords
40 Engineering, 46 Information and Computing Sciences, 4603 Computer Vision and Multimedia Computation
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Source
2025 IEEE/CVF International Conference on Computer Vision (ICCV)
Publisher
IEEE