663 citations · 3.7k across the 62 of their papers we have counts for
66 papers
OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation
Dongming Wu, Tiancai Wang, Yuang Zhang +2
Referring video object segmentation (RVOS) aims at segmenting an object in a video following human instruction. Current state-of-the-art methods fall into an offline pattern, in wh…
TextFormer: A Query-based End-to-End Text Spotter with Mixed Supervision
Yukun Zhai, Xiaoqiang Zhang, Xiameng Qin +3
End-to-end text spotting is a vital computer vision task that aims to integrate scene text detection and recognition into a unified framework. Typical methods heavily rely on Regio…
Language-Guided 3D Object Detection in Point Cloud for Autonomous Driving
Wenhao Cheng, Junbo Yin, Wei Li +2
This paper addresses the problem of 3D referring expression comprehension (REC) in autonomous driving scenario, which aims to ground a natural language to the targeted region in Li…
Weakly Supervised Monocular 3D Object Detection using Multi-View Projection and Direction Consistency
Runzhou Tao, Wencheng Han, Zhongying Qiu +2
Monocular 3D object detection has become a mainstream approach in automatic driving for its easy application. A prominent advantage is that it does not need LiDAR point clouds duri…
Referring Multi-Object Tracking
Dongming Wu, Wencheng Han, Tiancai Wang +3
Existing referring understanding tasks tend to involve the detection of a single text-referred object. In this paper, we propose a new and general referring understanding task, ter…
Generalized Few-Shot 3D Object Detection of LiDAR Point Cloud for Autonomous Driving
Jiawei Liu, Xingping Dong, Sanyuan Zhao +1
Recent years have witnessed huge successes in 3D object detection to recognize common objects for autonomous driving (e.g., vehicles and pedestrians). However, most methods rely he…
Adaptive Siamese Tracking with a Compact Latent Network
Xingping Dong, Jianbing Shen, Fatih Porikli +2
In this paper, we provide an intuitive viewing to simplify the Siamese-based trackers by converting the tracking task to a classification. Under this viewing, we perform an in-dept…
LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving
Xiang Li, Junbo Yin, Botian Shi +3
Image instance segmentation is a fundamental research topic in autonomous driving, which is crucial for scene understanding and road safety. Advanced learning-based approaches ofte…
SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud
Yan Wang, Junbo Yin, Wei Li +3
LiDAR-based 3D object detection is an indispensable task in advanced autonomous driving systems. Though impressive detection results have been achieved by superior 3D detectors, th…
Rethinking Clustering-Based Pseudo-Labeling for Unsupervised Meta-Learning
Xingping Dong, Jianbing Shen, Ling Shao
The pioneering method for unsupervised meta-learning, CACTUs, is a clustering-based approach with pseudo-labeling. This approach is model-agnostic and can be combined with supervis…
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds
Junbo Yin, Jianbing Shen, Xin Gao +2
Previous works for LiDAR-based 3D object detection mainly focus on the single-frame paradigm. In this paper, we propose to detect 3D objects by exploiting temporal information in m…
Semi-supervised 3D Object Detection with Proficient Teachers
Junbo Yin, Jin Fang, Dingfu Zhou +4
Dominated point cloud-based 3D object detectors in autonomous driving scenarios rely heavily on the huge amount of accurately labeled samples, however, 3D annotation in the point c…
ProposalContrast: Unsupervised Pre-training for LiDAR-based 3D Object Detection
Junbo Yin, Dingfu Zhou, Liangjun Zhang +4
Existing approaches for unsupervised point cloud pre-training are constrained to either scene-level or point/voxel-level instance discrimination. Scene-level methods tend to lose l…
Counterfactual Cycle-Consistent Learning for Instruction Following and Generation in Vision-Language Navigation
Hanqing Wang, Wei Liang, Jianbing Shen +2
Since the rise of vision-language navigation (VLN), great progress has been made in instruction following -- building a follower to navigate environments under the guidance of inst…
Tree Energy Loss: Towards Sparsely Annotated Semantic Segmentation
Zhiyuan Liang, Tiancai Wang, Xiangyu Zhang +2
Sparsely annotated semantic segmentation (SASS) aims to train a segmentation network with coarse-grained (i.e., point-, scribble-, and block-wise) supervisions, where only a small…
Consistency and Diversity induced Human Motion Segmentation
Tao Zhou, Huazhu Fu, Chen Gong +4
Subspace clustering is a classical technique that has been widely used for human motion segmentation and other related tasks. However, existing segmentation methods often cluster d…
Bilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answering
JianJian Cao, Xiameng Qin, Sanyuan Zhao +1
Answering semantically-complicated questions according to an image is challenging in Visual Question Answering (VQA) task. Although the image can be well represented by deep learni…
Full-Duplex Strategy for Video Object Segmentation
Ge-Peng Ji, Deng-Ping Fan, Keren Fu +3
Previous video object segmentation approaches mainly focus on using simplex solutions between appearance and motion, limiting feature collaboration efficiency among and across thes…
Face Forensics in the Wild
Tianfei Zhou, Wenguan Wang, Zhiyuan Liang +1
On existing public benchmarks, face forgery detection techniques have achieved great success. However, when used in multi-person videos, which often contain many people active in t…
Structured Scene Memory for Vision-Language Navigation
Hanqing Wang, Wenguan Wang, Wei Liang +2
Recently, numerous algorithms have been developed to tackle the problem of vision-language navigation (VLN), i.e., entailing an agent to navigate 3D environments through following…
Learning to Fuse Asymmetric Feature Maps in Siamese Trackers
Wencheng Han, Xingping Dong, Fahad Shahbaz Khan +2
Recently, Siamese-based trackers have achieved promising performance in visual tracking. Most recent Siamese-based trackers typically employ a depth-wise cross-correlation (DW-XCor…
Active Visual Information Gathering for Vision-Language Navigation
Hanqing Wang, Wenguan Wang, Tianmin Shu +2
Vision-language navigation (VLN) is the task of entailing an agent to carry out navigational instructions inside photo-realistic environments. One of the key challenges in VLN is h…
Siamese Network for RGB-D Salient Object Detection and Beyond
Keren Fu, Deng-Ping Fan, Ge-Peng Ji +3
Existing RGB-D salient object detection (SOD) models usually treat RGB and depth as independent information and design separate networks for feature extraction from each. Such sche…
RGB-D Salient Object Detection: A Survey
Tao Zhou, Deng-Ping Fan, Ming-Ming Cheng +2
Salient object detection (SOD), which simulates the human visual perception system to locate the most attractive object(s) in a scene, has been widely applied to various computer v…