no code implementations • NeurIPS 2020 • Zixuan Xu, Banghuai Li, Ye Yuan, Anhong Dang
What's more, to fully exploit Beta Representation, a novel pipeline Beta R-CNN equipped with BetaHead and BetaMask is proposed, leading to high detection performance in occluded and crowded scenes.
Ranked #11 on Pedestrian Detection on CityPersons
1 code implementation • 23 Oct 2022 • Zhuoxu Huang, Zhiyou Zhao, Banghuai Li, Jungong Han
Transformer with its underlying attention mechanism and the ability to capture long-range dependencies makes it become a natural choice for unordered point cloud data.
Ranked #1 on 3D Semantic Segmentation on SensatUrban
no code implementations • CVPR 2022 • Banghuai Li
We visualize each learned class representation in the feature space, and observe that some classes, especially under-represented scarce classes, are prone to cluster with analogous ones due to the lack of discriminative representation.
1 code implementation • 14 Dec 2021 • Jie Zhu, Huabin Huang, Banghuai Li, Leye Wang
In this paper, we notice that the class weights of categories that tend to share many adjacent boundary pixels lack discrimination, thereby limiting the performance.
no code implementations • 3 Dec 2021 • Jie Zhu, Huabin Huang, Banghuai Li, Yong liu, Leye Wang
Inspired by the generated sharp edges of superpixel blocks, we employ superpixel to guide the information passing within feature map.
no code implementations • 5 Nov 2021 • Lei Gan, Huabin Huang, Banghuai Li, Ye Yuan
In this paper, we present a novel add-on module, named Feature Balance Network (FBNet), to eliminate the feature camouflage in urban-scene segmentation.
3 code implementations • CVPR 2021 • Bo Sun, Banghuai Li, Shengcai Cai, Ye Yuan, Chi Zhang
We present Few-Shot object detection via Contrastive proposals Encoding (FSCE), a simple yet effective approach to learning contrastive-aware object proposal encodings that facilitate the classification of detected objects.
Ranked #13 on Few-Shot Object Detection on MS-COCO (30-shot)
1 code implementation • 7 Jul 2020 • Zixuan Xu, Banghuai Li, Miao Geng, Ye Yuan
Based on the prediction of each anchor template, we propose to aggregate the results, which can reduce the landmark uncertainty due to the large poses.
Ranked #1 on Face Alignment on AFLW-Full (Mean NME metric)