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Cong Yang

7 accepted papers

2026

Unleashing Semantic and Geometric Priors for 3D Scene Completion

AAAI 2026technical

Camera-based 3D semantic scene completion (SSC) provides dense geometric and semantic perception for autonomous driving and robotic navigation. However, existing methods rely on a coupled encoder to deliver both semantic and geometric priors, which forces the model to make a trade-off between confli

Cited by 0SourcePDFScholar
2025

A Light-Weight Framework for Open-Set Object Detection with Decoupled Feature Alignment in Joint Space

ICRA 2025

Open-set object detection (OSOD) is highly desirable for robotic manipulation in unstructured environments. However, existing OSOD methods often fail to meet the requirements of robotic applications due to their high computational burden and complex deployment. To address this issue, this paper prop

Cited by 2SourcecodeScholar
2024

A Vision-Centric Approach for Static Map Element Annotation

ICRA 2024poster

The recent development of online static map element (a.k.a. HD Map) construction algorithms has raised a vast demand for data with ground truth annotations. However, available public datasets currently cannot provide high-quality training data regarding consistency and accuracy. To this end, we pres…

Cited by 3SourcecodeScholar
2024

VRSO: Visual-Centric Reconstruction for Static Object Annotation

IROS 2024poster

As a part of the perception results of intelligent driving systems, static object detection (SOD) in 3D space provides crucial cues for driving environment understanding. With the rapid deployment of deep neural networks for SOD tasks, the demand for high-quality training samples soars. The traditio…

Cited by 0SourcecodeScholar
2020

CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization

ECCV 2020poster

Most current pipelines for spatiotemporal action localization connect frame-wise or clip-wise detection results to generate action proposals. In this paper, we propose Coarse-to-Fine Action Detector (CFAD), an original end-to-end trainable framework for efficient spatiotemporal action localization.…

Cited by 30SourcePDFScholar
2020

PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments

ECCV 2020poster

Object detection using an oriented bounding box (OBB) can better target rotated objects by reducing the overlap with background areas. Existing OBB approaches are mostly built on horizontal bounding box detectors by introducing an additional angle dimension optimized by a distance loss. However, as…