Search Results for author: Dingwen Zhang

Found 50 papers, 18 papers with code

SegGPT Meets Co-Saliency Scene

no code implementations8 May 2023 Yi Liu, Shoukun Xu, Dingwen Zhang, Jungong Han

Co-salient object detection targets at detecting co-existed salient objects among a group of images.

Co-Salient Object Detection object-detection +1

Boosting Low-Data Instance Segmentation by Unsupervised Pre-training with Saliency Prompt

no code implementations CVPR 2023 Hao Li, Dingwen Zhang, Nian Liu, Lechao Cheng, Yalun Dai, Chao Zhang, Xinggang Wang, Junwei Han

Inspired by the recent success of the Prompting technique, we introduce a new pre-training method that boosts QEIS models by giving Saliency Prompt for queries/kernels.

Instance Segmentation Semantic Segmentation +1

Combating Noisy Labels in Long-Tailed Image Classification

no code implementations1 Sep 2022 Chaowei Fang, Lechao Cheng, Huiyan Qi, Dingwen Zhang

Most existing methods that cope with noisy labels usually assume that the class distributions are well balanced, which has insufficient capacity to deal with the practical scenarios where training samples have imbalanced distributions.

Classification Image Classification

Deep 3D Vessel Segmentation based on Cross Transformer Network

1 code implementation22 Aug 2022 Chengwei Pan, Baolian Qi, Gangming Zhao, Jiaheng Liu, Chaowei Fang, Dingwen Zhang, Jinpeng Li

In CTN, a transformer module is constructed in parallel to a U-Net to learn long-distance dependencies between different anatomical regions; and these dependencies are communicated to the U-Net at multiple stages to endow it with global awareness.

Computed Tomography (CT) Segmentation

Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance

1 code implementation1 Jul 2022 Chengwei Pan, Gangming Zhao, Junjie Fang, Baolian Qi, Jiaheng Liu, Chaowei Fang, Dingwen Zhang, Jinpeng Li, Yizhou Yu

Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to much time and resource consumption.

Relational Reasoning Weakly-supervised Learning

Structured Attention Composition for Temporal Action Localization

2 code implementations20 May 2022 Le Yang, Junwei Han, Tao Zhao, Nian Liu, Dingwen Zhang

To tackle this issue, we make an early effort to study temporal action localization from the perspective of multi-modality feature learning, based on the observation that different actions exhibit specific preferences to appearance or motion modality.

Action Detection Temporal Action Localization

Hybrid Routing Transformer for Zero-Shot Learning

no code implementations29 Mar 2022 De Cheng, Gerong Wang, Bo wang, Qiang Zhang, Jungong Han, Dingwen Zhang

This design makes the presented transformer model a hybrid of 1) top-down and bottom-up attention pathways and 2) dynamic and static routing pathways.

Zero-Shot Learning

Cross-Modality High-Frequency Transformer for MR Image Super-Resolution

no code implementations29 Mar 2022 Chaowei Fang, Dingwen Zhang, Liang Wang, Yulun Zhang, Lechao Cheng, Junwei Han

Improving the resolution of magnetic resonance (MR) image data is critical to computer-aided diagnosis and brain function analysis.

Image Super-Resolution Vocal Bursts Intensity Prediction

Robust Single Image Dehazing Based on Consistent and Contrast-Assisted Reconstruction

no code implementations29 Mar 2022 De Cheng, Yan Li, Dingwen Zhang, Nannan Wang, Xinbo Gao, Jiande Sun

To properly address this problem, we propose a novel density-variational learning framework to improve the robustness of the image dehzing model assisted by a variety of negative hazy images, to better deal with various complex hazy scenarios.

Image Dehazing Single Image Dehazing

Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic Segmentation

1 code implementation19 Mar 2022 Junwen Pan, Pengfei Zhu, Kaihua Zhang, Bing Cao, Yu Wang, Dingwen Zhang, Junwei Han, QinGhua Hu

Semantic segmentation with limited annotations, such as weakly supervised semantic segmentation (WSSS) and semi-supervised semantic segmentation (SSSS), is a challenging task that has attracted much attention recently.

Pseudo Label Segmentation +3

Colar: Effective and Efficient Online Action Detection by Consulting Exemplars

1 code implementation CVPR 2022 Le Yang, Junwei Han, Dingwen Zhang

Based on the exemplar-consultation mechanism, the long-term dependencies can be captured by regarding historical frames as exemplars, while the category-level modeling can be achieved by regarding representative frames from a category as exemplars.

Online Action Detection

Cross-Modality Deep Feature Learning for Brain Tumor Segmentation

no code implementations7 Jan 2022 Dingwen Zhang, Guohai Huang, Qiang Zhang, Jungong Han, Junwei Han, Yizhou Yu

Recent advances in machine learning and prevalence of digital medical images have opened up an opportunity to address the challenging brain tumor segmentation (BTS) task by using deep convolutional neural networks.

Brain Tumor Segmentation Segmentation +1

Robust Region Feature Synthesizer for Zero-Shot Object Detection

1 code implementation CVPR 2022 Peiliang Huang, Junwei Han, De Cheng, Dingwen Zhang

Zero-shot object detection aims at incorporating class semantic vectors to realize the detection of (both seen and) unseen classes given an unconstrained test image.

Generalized Zero-Shot Object Detection object-detection +1

Incremental Cross-view Mutual Distillation for Self-supervised Medical CT Synthesis

no code implementations CVPR 2022 Chaowei Fang, Liang Wang, Dingwen Zhang, Jun Xu, Yixuan Yuan, Junwei Han

Under this circumstance, the models learned from different views can distill valuable knowledge to guide the learning processes of each other.

Self-Supervised Learning

Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition

no code implementations17 Dec 2021 Guangyu Guo, Longfei Han, Junwei Han, Dingwen Zhang

To this end, we make a pioneering effort to distill helpful knowledge from a heavy network model learned from high-resolution (HR) images to a compact network model that will handle LR images, thus advancing the current knowledge distillation technique with the novel pixel distillation.

Knowledge Distillation Model Compression +1

Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching

no code implementations17 Dec 2021 Dingwen Zhang, Wenyuan Zeng, Guangyu Guo, Chaowei Fang, Lechao Cheng, Ming-Ming Cheng, Junwei Han

Current weakly supervised semantic segmentation (WSSS) frameworks usually contain the separated mask-refinement model and the main semantic region mining model.

Knowledge Distillation Weakly supervised Semantic Segmentation +1

Background-Click Supervision for Temporal Action Localization

1 code implementation24 Nov 2021 Le Yang, Junwei Han, Tao Zhao, Tianwei Lin, Dingwen Zhang, Jianxin Chen

Weakly supervised temporal action localization aims at learning the instance-level action pattern from the video-level labels, where a significant challenge is action-context confusion.

Weakly-supervised Temporal Action Localization Weakly Supervised Temporal Action Localization

Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidance

1 code implementation2 Oct 2021 Nian Liu, Wangbo Zhao, Dingwen Zhang, Junwei Han, Ling Shao

On the other hand, instead of processing the twokinds of data separately, we build a novel dual graph modelto guide the focal stack fusion process using all-focus pat-terns.

Graph Learning Saliency Detection

Single Image Dehazing with An Independent Detail-Recovery Network

1 code implementation22 Sep 2021 Yan Li, De Cheng, Jiande Sun, Dingwen Zhang, Nannan Wang, Xinbo Gao

In this paper, we propose a single image dehazing method with an independent Detail Recovery Network (DRN), which considers capturing the details from the input image over a separate network and then integrates them into a coarse dehazed image.

Image Dehazing Single Image Dehazing

Strengthen Learning Tolerance for Weakly Supervised Object Localization

1 code implementation CVPR 2021 Guangyu Guo, Junwei Han, Fang Wan, Dingwen Zhang

Weakly supervised object localization (WSOL) aims at learning to localize objects of interest by only using the image-level labels as the supervision.

Weakly-Supervised Object Localization

A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentation

1 code implementation21 Apr 2021 Jie Lian, Jingyu Liu, Shu Zhang, Kai Gao, Xiaoqing Liu, Dingwen Zhang, Yizhou Yu

Leveraging on constant structure and disease relations extracted from domain knowledge, we propose a structure-aware relation network (SAR-Net) extending Mask R-CNN.

Instance Segmentation Object Detection +1

Weakly Supervised Object Localization and Detection: A Survey

no code implementations16 Apr 2021 Dingwen Zhang, Junwei Han, Gong Cheng, Ming-Hsuan Yang

As an emerging and challenging problem in the computer vision community, weakly supervised object localization and detection plays an important role for developing new generation computer vision systems and has received significant attention in the past decade.

Weakly-Supervised Object Localization

Few-Cost Salient Object Detection with Adversarial-Paced Learning

1 code implementation NeurIPS 2020 Dingwen Zhang, HaiBin Tian, Jungong Han

A fundamental challenge in training the existing deep saliency detection models is the requirement of large amounts of annotated data.

object-detection Object Detection +2

Onfocus Detection: Identifying Individual-Camera Eye Contact from Unconstrained Images

1 code implementation29 Mar 2021 Dingwen Zhang, Bo wang, Gerong Wang, Qiang Zhang, Jiajia Zhang, Jungong Han, Zheng You

Onfocus detection aims at identifying whether the focus of the individual captured by a camera is on the camera or not.

Densely Nested Top-Down Flows for Salient Object Detection

1 code implementation18 Feb 2021 Chaowei Fang, HaiBin Tian, Dingwen Zhang, Qiang Zhang, Jungong Han, Junwei Han

To this end, this paper revisits the role of top-down modeling in salient object detection and designs a novel densely nested top-down flows (DNTDF)-based framework.

object-detection Object Detection +1

Revisiting Anchor Mechanisms for Temporal Action Localization

1 code implementation22 Aug 2020 Le Yang, Houwen Peng, Dingwen Zhang, Jianlong Fu, Junwei Han

To address this problem, this paper proposes a novel anchor-free action localization module that assists action localization by temporal points.

Temporal Action Localization

Equivalent Classification Mapping for Weakly Supervised Temporal Action Localization

no code implementations18 Aug 2020 Tao Zhao, Junwei Han, Le Yang, Dingwen Zhang

The existing methods can be categorized into two localization-by-classification pipelines, i. e., the pre-classification pipeline and the post-classification pipeline.

Classification General Classification +2

Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection

1 code implementation7 Aug 2020 Chenglizhao Chen, Guotao Wang, Chong Peng, Dingwen Zhang, Yuming Fang, Hong Qin

In this way, even though the overall video saliency quality is heavily dependent on its spatial branch, however, the performance of the temporal branch still matter.

object-detection Salient Object Detection +2

Re-thinking Co-Salient Object Detection

2 code implementations7 Jul 2020 Deng-Ping Fan, Tengpeng Li, Zheng Lin, Ge-Peng Ji, Dingwen Zhang, Ming-Ming Cheng, Huazhu Fu, Jianbing Shen

CoSOD is an emerging and rapidly growing extension of salient object detection (SOD), which aims to detect the co-occurring salient objects in a group of images.

Benchmarking Co-Salient Object Detection +2

Reinforcement Cutting-Agent Learning for Video Object Segmentation

no code implementations CVPR 2018 Junwei Han, Le Yang, Dingwen Zhang, Xiaojun Chang, Xiaodan Liang

In this paper, we formulate this problem as a Markov Decision Process, where agents are learned to segment object regions under a deep reinforcement learning framework.

Decision Making Segmentation +4

Dilated Temporal Relational Adversarial Network for Generic Video Summarization

no code implementations30 Apr 2018 Yu-jia Zhang, Michael Kampffmeyer, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing

Specifically, DTR-GAN learns a dilated temporal relational generator and a discriminator with three-player loss in an adversarial manner.

Video Summarization Video Understanding

Unsupervised Object-Level Video Summarization with Online Motion Auto-Encoder

no code implementations2 Jan 2018 Yu-jia Zhang, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing

Unsupervised video summarization plays an important role on digesting, browsing, and searching the ever-growing videos every day, and the underlying fine-grained semantic and motion information (i. e., objects of interest and their key motions) in online videos has been barely touched.

Unsupervised Video Summarization

Supervision by Fusion: Towards Unsupervised Learning of Deep Salient Object Detector

no code implementations ICCV 2017 Dingwen Zhang, Junwei Han, Yu Zhang

Based on this insight, we combine an intra-image fusion stream and a inter-image fusion stream in the proposed framework to generate the learning curriculum and pseudo ground-truth for supervising the training of the deep salient object detector.

object-detection RGB Salient Object Detection +1

SPFTN: A Self-Paced Fine-Tuning Network for Segmenting Objects in Weakly Labelled Videos

no code implementations CVPR 2017 Dingwen Zhang, Le Yang, Deyu Meng, Dong Xu, Junwei Han

Object segmentation in weakly labelled videos is an interesting yet challenging task, which aims at learning to perform category-specific video object segmentation by only using video-level tags.

Semantic Segmentation Video Object Segmentation +2

Learning Category-Specific 3D Shape Models From Weakly Labeled 2D Images

no code implementations CVPR 2017 Dingwen Zhang, Junwei Han, Yang Yang, Dong Huang

Recently, researchers have made great processes to build category-specific 3D shape models from 2D images with manual annotations consisting of class labels, keypoints, and ground truth figure-ground segmentations.

3D Shape Reconstruction Segmentation +2

Object Co-Segmentation via Graph Optimized-Flexible Manifold Ranking

no code implementations CVPR 2016 Rong Quan, Junwei Han, Dingwen Zhang, Feiping Nie

Aiming at automatically discovering the common objects contained in a set of relevant images and segmenting them as foreground simultaneously, object co-segmentation has become an active research topic in recent years.


Co-Saliency Detection via Looking Deep and Wide

no code implementations CVPR 2015 Dingwen Zhang, Junwei Han, Chao Li, Jingdong Wang

In the proposed framework, the wide and deep information are explored for the object proposal windows extracted in each image, and the co-saliency scores are calculated by integrating the intra-image contrast and intra group consistency via a principled Bayesian formulation.

Co-Salient Object Detection Image Retrieval +1

Predicting Eye Fixations Using Convolutional Neural Networks

no code implementations CVPR 2015 Nian Liu, Junwei Han, Dingwen Zhang, Shifeng Wen, Tianming Liu

It is believed that eye movements in free-viewing of natural scenes are directed by both bottom-up visual saliency and top-down visual factors.

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