DDStereo: Efficient Dual Decoder Transformers for Stereo 3D Road Anomaly Detection

Key points

• This is the first stereo 3D detector to achieve real-time inference at 23.5 ms, at the level of monocular methods.
• The dual decoder separates foreground binary detection using disparity features from 3D attribute regression using left-view features.
• Shared object queries align the two decoders and produce anomaly scores without NMS or anchor matching.
• On the KITTI-AR-OoD open-set benchmark, it outperforms S3AD with 78.09% OoD AP3D on the R40 metric.
• It achieves SOTA compared with all existing stereo methods on the pedestrian and cyclist classes.
• Using only an additional 10% of synthetic data, it still reaches 54.65% OoD AP3D, far exceeding S3AD's 24.45% and showing strong generalization.

Paper links

External research summaries. These are not HDATF publications or measured product results.