353 citations · 1.5k across the 84 of their papers we have counts for
50 papers · 1 filter
Learning to Learn Better for Video Object Segmentation
Meng Lan, Jing Zhang, Lefei Zhang +1
Recently, the joint learning framework (JOINT) integrates matching based transductive reasoning and online inductive learning to achieve accurate and robust semi-supervised video o…
Localizing Scan Targets from Human Pose for Autonomous Lung Ultrasound Imaging
Jianzhi Long, Jicang Cai, Abdullah Al-Battal +4
Ultrasound is progressing toward becoming an affordable and versatile solution to medical imaging. With the advent of COVID-19 global pandemic, there is a need to fully automate ul…
ViTPose++: Vision Transformer for Generic Body Pose Estimation
Yufei Xu, Jing Zhang, Qiming Zhang +1
In this paper, we show the surprisingly good properties of plain vision transformers for body pose estimation from various aspects, namely simplicity in model structure, scalabilit…
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
Benjamin Kiefer, Matej Kristan, Janez Perš +70
The 1 Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and…
Unified Discrete Diffusion for Simultaneous Vision-Language Generation
Minghui Hu, Chuanxia Zheng, Heliang Zheng +5
The recently developed discrete diffusion models perform extraordinarily well in the text-to-image task, showing significant promise for handling the multi-modality signals. In thi…
Rethinking Hierarchies in Pre-trained Plain Vision Transformer
Yufei Xu, Jing Zhang, Qiming Zhang +1
Self-supervised pre-training vision transformer (ViT) via masked image modeling (MIM) has been proven very effective. However, customized algorithms should be carefully designed fo…
3DDesigner: Towards Photorealistic 3D Object Generation and Editing with Text-guided Diffusion Models
Gang Li, Heliang Zheng, Chaoyue Wang +3
Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we di…
SLLEN: Semantic-aware Low-light Image Enhancement Network
Mingye Ju, Chuheng Chen, Charles A. Guo +3
How to effectively explore semantic feature is vital for low-light image enhancement (LLE). Existing methods usually utilize the semantic feature that is only drawn from the output…
DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting
Maoyuan Ye, Jing Zhang, Shanshan Zhao +4
End-to-end text spotting aims to integrate scene text detection and recognition into a unified framework. Dealing with the relationship between the two sub-tasks plays a pivotal ro…
Unifying Flow, Stereo and Depth Estimation
Haofei Xu, Jing Zhang, Jianfei Cai +4
We present a unified formulation and model for three motion and 3D perception tasks: optical flow, rectified stereo matching and unrectified stereo depth estimation from posed imag…
Towards Robust Referring Image Segmentation
Jianzong Wu, Xiangtai Li, Xia Li +3
Referring Image Segmentation (RIS) is a fundamental vision-language task that outputs object masks based on text descriptions. Many works have achieved considerable progress for RI…
On Robust Cross-View Consistency in Self-Supervised Monocular Depth Estimation
Haimei Zhao, Jing Zhang, Zhuo Chen +2
Remarkable progress has been made in self-supervised monocular depth estimation (SS-MDE) by exploring cross-view consistency, e.g., photometric consistency and 3D point cloud consi…
Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection
Simin Li, Huangxinxin Xu, Jiakai Wang +4
Billions of people are sharing their daily life images on social media every day. However, their biometric information (e.g., fingerprint) could be easily stolen from these images.…
Grounded Affordance from Exocentric View
Hongchen Luo, Wei Zhai, Jing Zhang +2
Affordance grounding aims to locate objects' "action possibilities" regions, which is an essential step toward embodied intelligence. Due to the diversity of interactive affordance…
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model
Di Wang, Qiming Zhang, Yufei Xu +4
Large-scale vision foundation models have made significant progress in visual tasks on natural images, with vision transformers being the primary choice due to their good scalabili…
Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular Depth Estimation by Integrating IMU Motion Dynamics
Sen Zhang, Jing Zhang, Dacheng Tao
Unsupervised monocular depth and ego-motion estimation has drawn extensive research attention in recent years. Although current methods have reached a high up-to-scale accuracy, th…
ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning
Shengchao Hu, Li Chen, Penghao Wu +3
Many existing autonomous driving paradigms involve a multi-stage discrete pipeline of tasks. To better predict the control signals and enhance user safety, an end-to-end approach t…
JPerceiver: Joint Perception Network for Depth, Pose and Layout Estimation in Driving Scenes
Haimei Zhao, Jing Zhang, Sen Zhang +1
Depth estimation, visual odometry (VO), and bird's-eye-view (BEV) scene layout estimation present three critical tasks for driving scene perception, which is fundamental for motion…
ReAct: Temporal Action Detection with Relational Queries
Dingfeng Shi, Yujie Zhong, Qiong Cao +4
This work aims at advancing temporal action detection (TAD) using an encoder-decoder framework with action queries, similar to DETR, which has shown great success in object detecti…
Transformer-based Context Condensation for Boosting Feature Pyramids in Object Detection
Zhe Chen, Jing Zhang, Yufei Xu +1
Current object detectors typically have a feature pyramid (FP) module for multi-level feature fusion (MFF) which aims to mitigate the gap between features from different levels and…
Learning Graph Neural Networks for Image Style Transfer
Yongcheng Jing, Yining Mao, Yiding Yang +4
State-of-the-art parametric and non-parametric style transfer approaches are prone to either distorted local style patterns due to global statistics alignment, or unpleasing artifa…
DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer
Maoyuan Ye, Jing Zhang, Shanshan Zhao +3
Recently, Transformer-based methods, which predict polygon points or Bezier curve control points for localizing texts, are popular in scene text detection. However, these methods b…
SFNet: Faster and Accurate Semantic Segmentation via Semantic Flow
Xiangtai Li, Jiangning Zhang, Yibo Yang +4
In this paper, we focus on exploring effective methods for faster and accurate semantic segmentation. A common practice to improve the performance is to attain high-resolution feat…
GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation
Haibo Qiu, Baosheng Yu, Dacheng Tao
Point cloud semantic segmentation from projected views, such as range-view (RV) and bird's-eye-view (BEV), has been intensively investigated. Different views capture different info…