1.1k citations · 2.2k across the 55 of their papers we have counts for
31 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…
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…
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…
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…
Transformer Networks for Predictive Group Elevator Control
Jing Zhang, Athanasios Tsiligkaridis, Hiroshi Taguchi +2
We propose a Predictive Group Elevator Scheduler by using predictive information of passengers arrivals from a Transformer based destination predictor and a linear regression model…
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…
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…
CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal Pose
Xu Zhang, Wen Wang, Zhe Chen +3
Animal pose estimation is challenging for existing image-based methods because of limited training data and large intra- and inter-species variances. Motivated by the progress of v…
Toward Real-world Single Image Deraining: A New Benchmark and Beyond
Wei Li, Qiming Zhang, Jing Zhang +3
Single image deraining (SID) in real scenarios attracts increasing attention in recent years. Due to the difficulty in obtaining real-world rainy/clean image pairs, previous real d…
Referring Image Matting
Jizhizi Li, Jing Zhang, Dacheng Tao
Different from conventional image matting, which either requires user-defined scribbles/trimap to extract a specific foreground object or directly extracts all the foreground objec…
RU-Net: Regularized Unrolling Network for Scene Graph Generation
Xin Lin, Changxing Ding, Jing Zhang +2
Scene graph generation (SGG) aims to detect objects and predict the relationships between each pair of objects. Existing SGG methods usually suffer from several issues, including 1…
Multi-Task Learning with Multi-Query Transformer for Dense Prediction
Yangyang Xu, Xiangtai Li, Haobo Yuan +2
Previous multi-task dense prediction studies developed complex pipelines such as multi-modal distillations in multiple stages or searching for task relational contexts for each tas…
DearKD: Data-Efficient Early Knowledge Distillation for Vision Transformers
Xianing Chen, Qiong Cao, Yujie Zhong +3
Transformers are successfully applied to computer vision due to their powerful modeling capacity with self-attention. However, the excellent performance of transformers heavily dep…
ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation
Yufei Xu, Jing Zhang, Qiming Zhang +1
Although no specific domain knowledge is considered in the design, plain vision transformers have shown excellent performance in visual recognition tasks. However, little effort ha…
Learning to Purification for Unsupervised Person Re-identification
Long Lan, Xiao Teng, Jing Zhang +2
Unsupervised person re-identification is a challenging and promising task in computer vision. Nowadays unsupervised person re-identification methods have achieved great progress by…
VSA: Learning Varied-Size Window Attention in Vision Transformers
Qiming Zhang, Yufei Xu, Jing Zhang +1
Attention within windows has been widely explored in vision transformers to balance the performance, computation complexity, and memory footprint. However, current models adopt a h…
An Empirical Study of Remote Sensing Pretraining
Di Wang, Jing Zhang, Bo Du +2
Deep learning has largely reshaped remote sensing (RS) research for aerial image understanding and made a great success. Nevertheless, most of the existing deep models are initiali…