70 citations · 246 across the 19 of their papers we have counts for
19 papers
Fine-grained Text-Video Retrieval with Frozen Image Encoders
Zuozhuo Dai, Fangtao Shao, Qingkun Su +2
State-of-the-art text-video retrieval (TVR) methods typically utilize CLIP and cosine similarity for efficient retrieval. Meanwhile, cross attention methods, which employ a transfo…
UVOSAM: A Mask-free Paradigm for Unsupervised Video Object Segmentation via Segment Anything Model
Zhenghao Zhang, Shengfan Zhang, Zhichao Wei +2
The current state-of-the-art methods for unsupervised video object segmentation (UVOS) require extensive training on video datasets with mask annotations, limiting their effectiven…
3D Former: Monocular Scene Reconstruction with 3D SDF Transformers
Weihao Yuan, Xiaodong Gu, Heng Li +2
Monocular scene reconstruction from posed images is challenging due to the complexity of a large environment. Recent volumetric methods learn to directly predict the TSDF volume an…
Linguistic Query-Guided Mask Generation for Referring Image Segmentation
Zhichao Wei, Xiaohao Chen, Mingqiang Chen +1
Referring image segmentation aims to segment the image region of interest according to the given language expression, which is a typical multi-modal task. Existing methods either a…
RenderNet: Visual Relocalization Using Virtual Viewpoints in Large-Scale Indoor Environments
Jiahui Zhang, Shitao Tang, Kejie Qiu +6
Visual relocalization has been a widely discussed problem in 3D vision: given a pre-constructed 3D visual map, the 6 DoF (Degrees-of-Freedom) pose of a query image is estimated. Re…
RCP: Recurrent Closest Point for Scene Flow Estimation on 3D Point Clouds
Xiaodong Gu, Chengzhou Tang, Weihao Yuan +3
3D motion estimation including scene flow and point cloud registration has drawn increasing interest. Inspired by 2D flow estimation, recent methods employ deep neural networks to…
NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation
Weihao Yuan, Xiaodong Gu, Zuozhuo Dai +2
Estimating the accurate depth from a single image is challenging since it is inherently ambiguous and ill-posed. While recent works design increasingly complicated and powerful net…
QuadTree Attention for Vision Transformers
Shitao Tang, Jiahui Zhang, Siyu Zhu +1
Transformers have been successful in many vision tasks, thanks to their capability of capturing long-range dependency. However, their quadratic computational complexity poses a maj…
GB-CosFace: Rethinking Softmax-based Face Recognition from the Perspective of Open Set Classification
Lizhe Liu, Mingqiang Chen, Xiaohao Chen +2
State-of-the-art face recognition methods typically take the multi-classification pipeline and adopt the softmax-based loss for optimization. Although these methods have achieved g…
FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol Spotting
Zhiwen Fan, Lingjie Zhu, Honghua Li +3
Access to large and diverse computer-aided design (CAD) drawings is critical for developing symbol spotting algorithms. In this paper, we present FloorPlanCAD, a large-scale real-w…
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution
Lizhe Liu, Xiaohao Chen, Siyu Zhu +1
Modern deep-learning-based lane detection methods are successful in most scenarios but struggling for lane lines with complex topologies. In this work, we propose CondLaneNet, a no…
Stereo Matching by Self-supervision of Multiscopic Vision
Weihao Yuan, Yazhan Zhang, Bingkun Wu +4
Self-supervised learning for depth estimation possesses several advantages over supervised learning. The benefits of no need for ground-truth depth, online fine-tuning, and better…
Learning Camera Localization via Dense Scene Matching
Shitao Tang, Chengzhou Tang, Rui Huang +2
Camera localization aims to estimate 6 DoF camera poses from RGB images. Traditional methods detect and match interest points between a query image and a pre-built 3D model. Recent…
AR Mapping: Accurate and Efficient Mapping for Augmented Reality
Rui Huang, Chuan Fang, Kejie Qiu +4
Augmented reality (AR) has gained increasingly attention from both research and industry communities. By overlaying digital information and content onto the physical world, AR enab…
Compact 3D Map-Based Monocular Localization Using Semantic Edge Alignment
Kejie Qiu, Shenzhou Chen, Jiahui Zhang +4
Accurate localization is fundamental to a variety of applications, such as navigation, robotics, autonomous driving, and Augmented Reality (AR). Different from incremental localiza…
DRO: Deep Recurrent Optimizer for Video to Depth
Xiaodong Gu, Weihao Yuan, Zuozhuo Dai +4
There are increasing interests of studying the video-to-depth (V2D) problem with machine learning techniques. While earlier methods directly learn a mapping from images to depth ma…
Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs
Chuan Fang, Shuai Ding, Zilong Dong +3
The integration of multiple cameras and 3D Li- DARs has become basic configuration of augmented reality devices, robotics, and autonomous vehicles. The calibration of multi-modal s…
Cluster Contrast for Unsupervised Person Re-Identification
Zuozhuo Dai, Guangyuan Wang, Weihao Yuan +3
State-of-the-art unsupervised re-ID methods train the neural networks using a memory-based non-parametric softmax loss. Instance feature vectors stored in memory are assigned pseud…
Batch DropBlock Network for Person Re-identification and Beyond
Zuozhuo Dai, Mingqiang Chen, Xiaodong Gu +2
Since the person re-identification task often suffers from the problem of pose changes and occlusions, some attentive local features are often suppressed when training CNNs. In thi…