3 accepted papers
Multi-view 3D object detection plays a vital role in autonomous driving systems due to its ability to perceive complex scenes accurately. However, real-world driving data often exhibits a long-tailed distribution, causing significant drops in detection accuracy for rare categories in existing method
Due to the inherent ambiguity of facial expressions and subjectivity in dataset labeling, learning with noisy labels remains a critical challenge in facial expression recognition (FER). The supervisory mechanism of teacher-student network offers a promising approach for noisy-labeled FER. However, t
3D point cloud semantic segmentation has attracted wide attention with its extensive applications in autonomous driving, AR/VR, and robot sensing fields. However, in existing methods, each point in the segmentation results is predicted independently from each other. This property causes the non-cont…