36 citations · 149 across the 16 of their papers we have counts for
16 papers
PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection
Ming Nie, Yujing Xue, Chunwei Wang +7
Recently, polar-based representation has shown promising properties in perceptual tasks. In addition to Cartesian-based approaches, which separate point clouds unevenly, representi…
CLIP: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data
Yihan Zeng, Chenhan Jiang, Jiageng Mao +7
Contrastive Language-Image Pre-training, benefiting from large-scale unlabeled text-image pairs, has demonstrated great performance in open-world vision understanding tasks. Howeve…
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers
Xuyang Bai, Zeyu Hu, Xinge Zhu +4
LiDAR and camera are two important sensors for 3D object detection in autonomous driving. Despite the increasing popularity of sensor fusion in this field, the robustness against i…
Adversarial Robustness under Long-Tailed Distribution
Tong Wu, Ziwei Liu, Qingqiu Huang +2
Adversarial robustness has attracted extensive studies recently by revealing the vulnerability and intrinsic characteristics of deep networks. However, existing works on adversaria…
A Unified Framework for Shot Type Classification Based on Subject Centric Lens
Anyi Rao, Jiaze Wang, Linning Xu +4
Shots are key narrative elements of various videos, e.g. movies, TV series, and user-generated videos that are thriving over the Internet. The types of shots greatly influence how…
Online Multi-modal Person Search in Videos
Jiangyue Xia, Anyi Rao, Qingqiu Huang +3
The task of searching certain people in videos has seen increasing potential in real-world applications, such as video organization and editing. Most existing approaches are devise…
MovieNet: A Holistic Dataset for Movie Understanding
Qingqiu Huang, Yu Xiong, Anyi Rao +2
Recent years have seen remarkable advances in visual understanding. However, how to understand a story-based long video with artistic styles, e.g. movie, remains challenging. In th…
Learn to Propagate Reliably on Noisy Affinity Graphs
Lei Yang, Qingqiu Huang, Huaiyi Huang +2
Recent works have shown that exploiting unlabeled data through label propagation can substantially reduce the labeling cost, which has been a critical issue in developing visual re…
Placepedia: Comprehensive Place Understanding with Multi-Faceted Annotations
Huaiyi Huang, Yuqi Zhang, Qingqiu Huang +3
Place is an important element in visual understanding. Given a photo of a building, people can often tell its functionality, e.g. a restaurant or a shop, its cultural style, e.g. A…
Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets
Tong Wu, Qingqiu Huang, Ziwei Liu +2
We present a new loss function called Distribution-Balanced Loss for the multi-label recognition problems that exhibit long-tailed class distributions. Compared to conventional sin…
A Local-to-Global Approach to Multi-modal Movie Scene Segmentation
Anyi Rao, Linning Xu, Yu Xiong +4
Scene, as the crucial unit of storytelling in movies, contains complex activities of actors and their interactions in a physical environment. Identifying the composition of scenes…
A Graph-Based Framework to Bridge Movies and Synopses
Yu Xiong, Qingqiu Huang, Lingfeng Guo +3
Inspired by the remarkable advances in video analytics, research teams are stepping towards a greater ambition -- movie understanding. However, compared to those activity videos in…
WIDER Face and Pedestrian Challenge 2018: Methods and Results
Chen Change Loy, Dahua Lin, Wanli Ouyang +49
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurat…
Person Search in Videos with One Portrait Through Visual and Temporal Links
Qingqiu Huang, Wentao Liu, Dahua Lin
In real-world applications, e.g. law enforcement and video retrieval, one often needs to search a certain person in long videos with just one portrait. This is much more challengin…
From Trailers to Storylines: An Efficient Way to Learn from Movies
Qingqiu Huang, Yuanjun Xiong, Yu Xiong +2
The millions of movies produced in the human history are valuable resources for computer vision research. However, learning a vision model from movie data would meet with serious d…
Unifying Identification and Context Learning for Person Recognition
Qingqiu Huang, Yu Xiong, Dahua Lin
Despite the great success of face recognition techniques, recognizing persons under unconstrained settings remains challenging. Issues like profile views, unfavorable lighting, and…