5 citations · 11 across the 11 of their papers we have counts for
12 papers
DAMap: Distance-aware MapNet for High Quality HD Map Construction
Jinpeng Dong, Chen Li, Yutong Lin +3
Predicting High-definition (HD) map elements with high quality (high classification and localization scores) is crucial to the safety of autonomous driving vehicles. However, curre…
FreqPDE: Rethinking Positional Depth Embedding for Multi-View 3D Object Detection Transformers
Haisheng Su, Junjie Zhang, Feixiang Song +4
Detecting 3D objects accurately from multi-view 2D images is a challenging yet essential task in the field of autonomous driving. Current methods resort to integrating depth predic…
StructVPR++: Distill Structural and Semantic Knowledge with Weighting Samples for Visual Place Recognition
Yanqing Shen, Sanping Zhou, Jingwen Fu +3
Visual place recognition is a challenging task for autonomous driving and robotics, which is usually considered as an image retrieval problem. A commonly used two-stage strategy in…
PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation
Ning Gao, Sanping Zhou, Le Wang +1
Semi-supervised learning has emerged as a widely adopted technique in the field of medical image segmentation. The existing works either focuses on the construction of consistency…
Robust Noisy Label Learning via Two-Stream Sample Distillation
Sihan Bai, Sanping Zhou, Zheng Qin +2
Noisy label learning aims to learn robust networks under the supervision of noisy labels, which plays a critical role in deep learning. Existing work either conducts sample selecti…
Molecule Design by Latent Prompt Transformer
Deqian Kong, Yuhao Huang, Jianwen Xie +8
This work explores the challenging problem of molecule design by framing it as a conditional generative modeling task, where target biological properties or desired chemical constr…
FFINet: Future Feedback Interaction Network for Motion Forecasting
Miao Kang, Shengqi Wang, Sanping Zhou +3
Motion forecasting plays a crucial role in autonomous driving, with the aim of predicting the future reasonable motions of traffic agents. Most existing methods mainly model the hi…
Molecule Design by Latent Prompt Transformer
Deqian Kong, Yuhao Huang, Jianwen Xie +1
This paper proposes a latent prompt Transformer model for solving challenging optimization problems such as molecule design, where the goal is to find molecules with optimal values…
MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection
Zewei Lin, Yanqing Shen, Sanping Zhou +2
In this paper, we propose a novel and effective Multi-Level Fusion network, named as MLF-DET, for high-performance cross-modal 3D object DETection, which integrates both the featur…
Voxel or Pillar: Exploring Efficient Point Cloud Representation for 3D Object Detection
Yuhao Huang, Sanping Zhou, Junjie Zhang +2
Efficient representation of point clouds is fundamental for LiDAR-based 3D object detection. While recent grid-based detectors often encode point clouds into either voxels or pilla…
StructVPR: Distill Structural Knowledge with Weighting Samples for Visual Place Recognition
Yanqing Shen, Sanping Zhou, Jingwen Fu +3
Visual place recognition (VPR) is usually considered as a specific image retrieval problem. Limited by existing training frameworks, most deep learning-based works cannot extract s…
TransVPR: Transformer-based place recognition with multi-level attention aggregation
Ruotong Wang, Yanqing Shen, Weiliang Zuo +2
Visual place recognition is a challenging task for applications such as autonomous driving navigation and mobile robot localization. Distracting elements presenting in complex scen…