Search Results for author: Ming-Ming Cheng

Found 105 papers, 58 papers with code

VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder

no code implementations13 May 2022 YuChao Gu, Xintao Wang, Liangbin Xie, Chao Dong, Gen Li, Ying Shan, Ming-Ming Cheng

Equipped with the VQ codebook as a facial detail dictionary and the parallel decoder design, the proposed VQFR can largely enhance the restored quality of facial details while keeping the fidelity to previous methods.

Blind Face Restoration Quantization

Localization Distillation for Object Detection

1 code implementation12 Apr 2022 Zhaohui Zheng, Rongguang Ye, Qibin Hou, Dongwei Ren, Ping Wang, WangMeng Zuo, Ming-Ming Cheng

Second, we introduce the concept of valuable localization region that can aid to selectively distill the classification and localization knowledge for a certain region.

Knowledge Distillation Object Detection

Towards An End-to-End Framework for Flow-Guided Video Inpainting

1 code implementation6 Apr 2022 Zhen Li, Cheng-Ze Lu, Jianhua Qin, Chun-Le Guo, Ming-Ming Cheng

Optical flow, which captures motion information across frames, is exploited in recent video inpainting methods through propagating pixels along its trajectories.

Optical Flow Estimation Video Inpainting

Interactive Style Transfer: All is Your Palette

no code implementations25 Mar 2022 Zheng Lin, Zhao Zhang, Kang-Rui Zhang, Bo Ren, Ming-Ming Cheng

Our IST method can serve as a brush, dip style from anywhere, and then paint to any region of the target content image.

Style Transfer

Representation Compensation Networks for Continual Semantic Segmentation

1 code implementation10 Mar 2022 Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, Ming-Ming Cheng

In this work, we study the continual semantic segmentation problem, where the deep neural networks are required to incorporate new classes continually without catastrophic forgetting.

class-incremental learning Continual Semantic Segmentation +15

Visual Attention Network

7 code implementations20 Feb 2022 Meng-Hao Guo, Cheng-Ze Lu, Zheng-Ning Liu, Ming-Ming Cheng, Shi-Min Hu

In this paper, we propose a novel large kernel attention (LKA) module to enable self-adaptive and long-range correlations in self-attention while avoiding the above issues.

Image Classification Instance Segmentation +2

Deeply Explain CNN via Hierarchical Decomposition

no code implementations23 Jan 2022 Ming-Ming Cheng, Peng-Tao Jiang, Ling-Hao Han, Liang Wang, Philip Torr

The proposed framework can generate a deep hierarchy of strongly associated supporting evidence for the network decision, which provides insight into the decision-making process.

Decision Making

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

Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition

1 code implementation23 Jun 2021 Qibin Hou, Zihang Jiang, Li Yuan, Ming-Ming Cheng, Shuicheng Yan, Jiashi Feng

By realizing the importance of the positional information carried by 2D feature representations, unlike recent MLP-like models that encode the spatial information along the flattened spatial dimensions, Vision Permutator separately encodes the feature representations along the height and width dimensions with linear projections.

LayerCAM: Exploring Hierarchical Class Activation Maps for Localization

2 code implementations IEEE 2021 Peng-Tao Jiang, Chang-Bin Zhang, Qibin Hou, Ming-Ming Cheng, Yunchao Wei

To evaluate the quality of the class activation maps produced by LayerCAM, we apply them to weakly-supervised object localization and semantic segmentation.

Semantic Segmentation Weakly-Supervised Object Localization

Representative Batch Normalization With Feature Calibration

no code implementations CVPR 2021 Shang-Hua Gao, Qi Han, Duo Li, Ming-Ming Cheng, Pai Peng

We propose to add a simple yet effective feature calibration scheme into the centering and scaling operations of BatchNorm, enhancing the instance-specific representations with the negligible computational cost.

On the Connection between Local Attention and Dynamic Depth-wise Convolution

1 code implementation ICLR 2022 Qi Han, Zejia Fan, Qi Dai, Lei Sun, Ming-Ming Cheng, Jiaying Liu, Jingdong Wang

Sparse connectivity: there is no connection across channels, and each position is connected to the positions within a small local window.

Object Detection Semantic Segmentation

Large-scale Unsupervised Semantic Segmentation

no code implementations6 Jun 2021 ShangHua Gao, Zhong-Yu Li, Ming-Hsuan Yang, Ming-Ming Cheng, Junwei Han, Philip Torr

Powered by the ImageNet dataset, unsupervised learning on large-scale data has made significant advances for classification tasks.

Representation Learning Unsupervised Semantic Segmentation

Unsupervised Scale-consistent Depth Learning from Video

2 code implementations25 May 2021 Jia-Wang Bian, Huangying Zhan, Naiyan Wang, Zhichao Li, Le Zhang, Chunhua Shen, Ming-Ming Cheng, Ian Reid

We propose a monocular depth estimator SC-Depth, which requires only unlabelled videos for training and enables the scale-consistent prediction at inference time.

Monocular Depth Estimation Monocular Visual Odometry +1

Salient Objects in Clutter

2 code implementations7 May 2021 Deng-Ping Fan, Jing Zhang, Gang Xu, Ming-Ming Cheng, Ling Shao

This design bias has led to a saturation in performance for state-of-the-art SOD models when evaluated on existing datasets.

Image Augmentation Object Detection +2

Temporal Modulation Network for Controllable Space-Time Video Super-Resolution

1 code implementation CVPR 2021 Gang Xu, Jun Xu, Zhen Li, Liang Wang, Xing Sun, Ming-Ming Cheng

To well exploit the temporal information, we propose a Locally-temporal Feature Comparison (LFC) module, along with the Bi-directional Deformable ConvLSTM, to extract short-term and long-term motion cues in videos.

Frame Space-time Video Super-resolution +1

Low-Light Image and Video Enhancement Using Deep Learning: A Survey

3 code implementations21 Apr 2021 Chongyi Li, Chunle Guo, Linghao Han, Jun Jiang, Ming-Ming Cheng, Jinwei Gu, Chen Change Loy

Low-light image enhancement (LLIE) aims at improving the perception or interpretability of an image captured in an environment with poor illumination.

Face Detection Low-Light Image Enhancement +1

Localization Distillation for Dense Object Detection

2 code implementations24 Feb 2021 Zhaohui Zheng, Rongguang Ye, Ping Wang, Dongwei Ren, WangMeng Zuo, Qibin Hou, Ming-Ming Cheng

Previous KD methods for object detection mostly focus on imitating deep features within the imitation regions instead of mimicking classification logit due to its inefficiency in distilling localization information and trivial improvement.

Dense Object Detection Knowledge Distillation

Concealed Object Detection

1 code implementation20 Feb 2021 Deng-Ping Fan, Ge-Peng Ji, Ming-Ming Cheng, Ling Shao

We present the first systematic study on concealed object detection (COD), which aims to identify objects that are "perfectly" embedded in their background.

 Ranked #1 on Camouflaged Object Segmentation on CAMO (using extra training data)

Camouflaged Object Segmentation

Global2Local: Efficient Structure Search for Video Action Segmentation

1 code implementation CVPR 2021 Shang-Hua Gao, Qi Han, Zhong-Yu Li, Pai Peng, Liang Wang, Ming-Ming Cheng

Our search scheme exploits both global search to find the coarse combinations and local search to get the refined receptive field combination patterns further.

Action Segmentation

iNAS: Integral NAS for Device-Aware Salient Object Detection

no code implementations ICCV 2021 Yu-Chao Gu, Shang-Hua Gao, Xu-Sheng Cao, Peng Du, Shao-Ping Lu, Ming-Ming Cheng

Existing salient object detection (SOD) models usually focus on either backbone feature extractors or saliency heads, ignoring their relations.

Neural Architecture Search Object Detection +1

MobileSal: Extremely Efficient RGB-D Salient Object Detection

1 code implementation24 Dec 2020 Yu-Huan Wu, Yun Liu, Jun Xu, Jia-Wang Bian, Yu-Chao Gu, Ming-Ming Cheng

Therefore, we propose an implicit depth restoration (IDR) technique to strengthen the mobile networks' feature representation capability for RGB-D SOD.

RGB-D Salient Object Detection Salient Object Detection

EDN: Salient Object Detection via Extremely-Downsampled Network

1 code implementation24 Dec 2020 Yu-Huan Wu, Yun Liu, Le Zhang, Ming-Ming Cheng, Bo Ren

In this paper, we tap into this gap and show that enhancing high- level features is essential for SOD as well.

Object Detection Object Localization +1

Centralized Information Interaction for Salient Object Detection

no code implementations21 Dec 2020 Jiang-Jiang Liu, Zhi-Ang Liu, Ming-Ming Cheng

Our approach can cooperate with various existing U-shape-based salient object detection methods by substituting the connections between the bottom-up and top-down pathways.

Object Detection Salient Object Detection +1

ICNet: Intra-saliency Correlation Network for Co-Saliency Detection

1 code implementation NeurIPS 2020 Wen-Da Jin, Jun Xu, Ming-Ming Cheng, Yi Zhang, Wei Guo

Intra-saliency and inter-saliency cues have been extensively studied for co-saliency detection (Co-SOD).

Saliency Detection

Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images

2 code implementations26 Nov 2020 Qijian Zhang, Runmin Cong, Chongyi Li, Ming-Ming Cheng, Yuming Fang, Xiaochun Cao, Yao Zhao, Sam Kwong

Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains an open and challenging problem.

Object Detection Salient Object Detection

Delving Deep into Label Smoothing

2 code implementations25 Nov 2020 Chang-Bin Zhang, Peng-Tao Jiang, Qibin Hou, Yunchao Wei, Qi Han, Zhen Li, Ming-Ming Cheng

Experiments demonstrate that based on the same classification models, the proposed approach can effectively improve the classification performance on CIFAR-100, ImageNet, and fine-grained datasets.

Classification General Classification

Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation

1 code implementation10 Sep 2020 Yun Liu, Yu-Huan Wu, Pei-Song Wen, Yu-Jun Shi, Yu Qiu, Ming-Ming Cheng

For each proposal, this MIL framework can simultaneously compute probability distributions and category-aware semantic features, with which we can formulate a large undirected graph.

Image-level Supervised Instance Segmentation Multiple Instance Learning +2

Generalized Zero-Shot Learning via VAE-Conditioned Generative Flow

1 code implementation1 Sep 2020 Yu-Chao Gu, Le Zhang, Yun Liu, Shao-Ping Lu, Ming-Ming Cheng

Recent generative methods formulate GZSL as a missing data problem, which mainly adopts GANs or VAEs to generate visual features for unseen classes.

Generalized Zero-Shot Learning

Regularized Densely-connected Pyramid Network for Salient Instance Segmentation

1 code implementation28 Aug 2020 Yu-Huan Wu, Yun Liu, Le Zhang, Wang Gao, Ming-Ming Cheng

Much of the recent efforts on salient object detection (SOD) have been devoted to producing accurate saliency maps without being aware of their instance labels.

Instance Segmentation RGB Salient Object Detection +2

RGB-D Salient Object Detection: A Survey

9 code implementations1 Aug 2020 Tao Zhou, Deng-Ping Fan, Ming-Ming Cheng, Jianbing Shen, Ling Shao

Further, considering that the light field can also provide depth maps, we review SOD models and popular benchmark datasets from this domain as well.

RGB-D Salient Object Detection RGB Salient Object Detection +1

Geometric Style Transfer

no code implementations10 Jul 2020 Xiao-Chang Liu, Xuan-Yi Li, Ming-Ming Cheng, Peter Hall

Our contribution is to introduce a neural architecture that supports transfer of geometric style.

Style Transfer

Semi-Supervised Learning with Meta-Gradient

1 code implementation8 Jul 2020 Xin-Yu Zhang, Taihong Xiao, HaoLin Jia, Ming-Ming Cheng, Ming-Hsuan Yang

In this work, we propose a simple yet effective meta-learning algorithm in semi-supervised learning.


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.

Co-Salient Object Detection Salient Object Detection

Interactive Knowledge Distillation

no code implementations3 Jul 2020 Shipeng Fu, Zhen Li, Jun Xu, Ming-Ming Cheng, Zitao Liu, Xiaomin Yang

Knowledge distillation is a standard teacher-student learning framework to train a light-weight student network under the guidance of a well-trained large teacher network.

Knowledge Distillation

MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation

1 code implementation16 Jun 2020 Shijie Li, Yazan Abu Farha, Yun Liu, Ming-Ming Cheng, Juergen Gall

Despite the capabilities of these approaches in capturing temporal dependencies, their predictions suffer from over-segmentation errors.

Action Segmentation

Dependency Aware Filter Pruning

no code implementations6 May 2020 Kai Zhao, Xin-Yu Zhang, Qi Han, Ming-Ming Cheng

Convolutional neural networks (CNNs) are typically over-parameterized, bringing considerable computational overhead and memory footprint in inference.

Gradient-Induced Co-Saliency Detection

1 code implementation ECCV 2020 Zhao Zhang, Wenda Jin, Jun Xu, Ming-Ming Cheng

Co-saliency detection (Co-SOD) aims to segment the common salient foreground in a group of relevant images.

Co-Salient Object Detection

Conditional Variational Image Deraining

1 code implementation23 Apr 2020 Ying-Jun Du, Jun Xu, Xian-Tong Zhen, Ming-Ming Cheng, Ling Shao

In this paper, we propose a Conditional Variational Image Deraining (CVID) network for better deraining performance, leveraging the exclusive generative ability of Conditional Variational Auto-Encoder (CVAE) on providing diverse predictions for the rainy image.

Density Estimation Rain Removal

Dynamic Feature Integration for Simultaneous Detection of Salient Object, Edge and Skeleton

no code implementations18 Apr 2020 Jiang-Jiang Liu, Qibin Hou, Ming-Ming Cheng

To evaluate the performance of our proposed network on these tasks, we conduct exhaustive experiments on multiple representative datasets.

Edge Detection Semantic Segmentation

JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation

1 code implementation15 Apr 2020 Yu-Huan Wu, Shang-Hua Gao, Jie Mei, Jun Xu, Deng-Ping Fan, Rong-Guo Zhang, Ming-Ming Cheng

The chest CT scan test provides a valuable complementary tool to the RT-PCR test, and it can identify the patients in the early-stage with high sensitivity.

COVID-19 Diagnosis General Classification

Spatial Information Guided Convolution for Real-Time RGBD Semantic Segmentation

1 code implementation9 Apr 2020 Lin-Zhuo Chen, Zheng Lin, Ziqin Wang, Yong-Liang Yang, Ming-Ming Cheng

S-Conv is competent to infer the sampling offset of the convolution kernel guided by the 3D spatial information, helping the convolutional layer adjust the receptive field and adapt to geometric transformations.

Semantic Segmentation

Strip Pooling: Rethinking Spatial Pooling for Scene Parsing

2 code implementations CVPR 2020 Qibin Hou, Li Zhang, Ming-Ming Cheng, Jiashi Feng

Spatial pooling has been proven highly effective in capturing long-range contextual information for pixel-wise prediction tasks, such as scene parsing.

Scene Parsing Semantic Segmentation

Highly Efficient Salient Object Detection with 100K Parameters

1 code implementation ECCV 2020 Shang-Hua Gao, Yong-Qiang Tan, Ming-Ming Cheng, Chengze Lu, Yunpeng Chen, Shuicheng Yan

Salient object detection models often demand a considerable amount of computation cost to make precise prediction for each pixel, making them hardly applicable on low-power devices.

RGB Salient Object Detection Salient Object Detection

Deep Hough Transform for Semantic Line Detection

1 code implementation ECCV 2020 Kai Zhao, Qi Han, Chang-Bin Zhang, Jun Xu, Ming-Ming Cheng

In addition to the proposed method, we design an evaluation metric to assess the quality of line detection and construct a large scale dataset for the line detection task.

Line Detection

Structured Sparsification with Joint Optimization of Group Convolution and Channel Shuffle

1 code implementation19 Feb 2020 Xin-Yu Zhang, Kai Zhao, Taihong Xiao, Ming-Ming Cheng, Ming-Hsuan Yang

Recent advances in convolutional neural networks(CNNs) usually come with the expense of excessive computational overhead and memory footprint.

Network Pruning

Ordered or Orderless: A Revisit for Video based Person Re-Identification

no code implementations24 Dec 2019 Le Zhang, Zenglin Shi, Joey Tianyi Zhou, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Zeng Zeng, Chunhua Shen

Specifically, with a diagnostic analysis, we show that the recurrent structure may not be effective to learn temporal dependencies than what we expected and implicitly yields an orderless representation.

Video-Based Person Re-Identification

AdaSample: Adaptive Sampling of Hard Positives for Descriptor Learning

no code implementations27 Nov 2019 Xin-Yu Zhang, Le Zhang, Zao-Yi Zheng, Yun Liu, Jia-Wang Bian, Ming-Ming Cheng

The effectiveness of the triplet loss heavily relies on the triplet selection, in which a common practice is to first sample intra-class patches (positives) from the dataset for batch construction and then mine in-batch negatives to form triplets.


Towards Disentangling Non-Robust and Robust Components in Performance Metric

no code implementations25 Sep 2019 Yujun Shi, Benben Liao, Guangyong Chen, Yun Liu, Ming-Ming Cheng, Jiashi Feng

Then, we show by experiments that DNNs under standard training rely heavily on optimizing the non-robust component in achieving decent performance.

Adversarial Robustness

Image Inpainting with Learnable Bidirectional Attention Maps

1 code implementation ICCV 2019 Chaohao Xie, Shaohui Liu, Chao Li, Ming-Ming Cheng, WangMeng Zuo, Xiao Liu, Shilei Wen, Errui Ding

Most convolutional network (CNN)-based inpainting methods adopt standard convolution to indistinguishably treat valid pixels and holes, making them limited in handling irregular holes and more likely to generate inpainting results with color discrepancy and blurriness.

Image Inpainting

Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video

2 code implementations NeurIPS 2019 Jia-Wang Bian, Zhichao Li, Naiyan Wang, Huangying Zhan, Chunhua Shen, Ming-Ming Cheng, Ian Reid

To the best of our knowledge, this is the first work to show that deep networks trained using unlabelled monocular videos can predict globally scale-consistent camera trajectories over a long video sequence.

Ranked #32 on Monocular Depth Estimation on KITTI Eigen split (using extra training data)

Depth And Camera Motion Monocular Depth Estimation +1

An Evaluation of Feature Matchers for Fundamental Matrix Estimation

no code implementations26 Aug 2019 Jia-Wang Bian, Yu-Huan Wu, Ji Zhao, Yun Liu, Le Zhang, Ming-Ming Cheng, Ian Reid

According to this, we propose three high-quality matching systems and a Coarse-to-Fine RANSAC estimator.

Robust Regression via Deep Negative Correlation Learning

no code implementations24 Aug 2019 Le Zhang, Zenglin Shi, Ming-Ming Cheng, Yun Liu, Jia-Wang Bian, Joey Tianyi Zhou, Guoyan Zheng, Zeng Zeng

Nonlinear regression has been extensively employed in many computer vision problems (e. g., crowd counting, age estimation, affective computing).

Age Estimation Crowd Counting +1

EGNet:Edge Guidance Network for Salient Object Detection

no code implementations22 Aug 2019 Jia-Xing Zhao, Jiang-Jiang Liu, Den-Ping Fan, Yang Cao, Jufeng Yang, Ming-Ming Cheng

In the second step, we integrate the local edge information and global location information to obtain the salient edge features.

RGB Salient Object Detection Salient Object Detection

Scoot: A Perceptual Metric for Facial Sketches

1 code implementation ICCV 2019 Deng-Ping Fan, Shengchuan Zhang, Yu-Huan Wu, Yun Liu, Ming-Ming Cheng, Bo Ren, Paul L. Rosin, Rongrong Ji

In this paper, we design a perceptual metric, called Structure Co-Occurrence Texture (Scoot), which simultaneously considers the block-level spatial structure and co-occurrence texture statistics.

Face Sketch Synthesis SSIM

Image Formation Model Guided Deep Image Super-Resolution

1 code implementation18 Aug 2019 Jinshan Pan, Yang Liu, Deqing Sun, Jimmy Ren, Ming-Ming Cheng, Jian Yang, Jinhui Tang

We present a simple and effective image super-resolution algorithm that imposes an image formation constraint on the deep neural networks via pixel substitution.

Image Super-Resolution

Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image

1 code implementation17 Jun 2019 Jun Xu, Yuan Huang, Ming-Ming Cheng, Li Liu, Fan Zhu, Zhou Xu, Ling Shao

A simple but useful observation on our NAC is: as long as the noise is weak, it is feasible to learn a self-supervised network only with the corrupted image, approximating the optimal parameters of a supervised network learned with pairs of noisy and clean images.

Image Denoising

Understanding Adversarial Behavior of DNNs by Disentangling Non-Robust and Robust Components in Performance Metric

no code implementations6 Jun 2019 Yujun Shi, Benben Liao, Guangyong Chen, Yun Liu, Ming-Ming Cheng, Jiashi Feng

Despite many previous works studying the reason behind such adversarial behavior, the relationship between the generalization performance and adversarial behavior of DNNs is still little understood.

Adversarial Robustness

LSANet: Feature Learning on Point Sets by Local Spatial Aware Layer

1 code implementation14 May 2019 Lin-Zhuo Chen, Xuan-Yi Li, Deng-Ping Fan, Kai Wang, Shao-Ping Lu, Ming-Ming Cheng

We design a novel Local Spatial Aware (LSA) layer, which can learn to generate Spatial Distribution Weights (SDWs) hierarchically based on the spatial relationship in local region for spatial independent operations, to establish the relationship between these operations and spatial distribution, thus capturing the local geometric structure sensitively. We further propose the LSANet, which is based on LSA layer, aggregating the spatial information with associated features in each layer of the network better in network design. The experiments show that our LSANet can achieve on par or better performance than the state-of-the-art methods when evaluating on the challenging benchmark datasets.

A Simple Pooling-Based Design for Real-Time Salient Object Detection

5 code implementations CVPR 2019 Jiang-Jiang Liu, Qibin Hou, Ming-Ming Cheng, Jiashi Feng, Jianmin Jiang

We further design a feature aggregation module (FAM) to make the coarse-level semantic information well fused with the fine-level features from the top-down pathway.

RGB Salient Object Detection Salient Object Detection

Res2Net: A New Multi-scale Backbone Architecture

18 code implementations2 Apr 2019 Shang-Hua Gao, Ming-Ming Cheng, Kai Zhao, Xin-Yu Zhang, Ming-Hsuan Yang, Philip Torr

We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e. g., CIFAR-100 and ImageNet.

Image Classification Instance Segmentation +2

DNA: Deeply-supervised Nonlinear Aggregation for Salient Object Detection

1 code implementation28 Mar 2019 Yun Liu, Ming-Ming Cheng, Xin-Yu Zhang, Guang-Yu Nie, Meng Wang

Recent progress on salient object detection mainly aims at exploiting how to effectively integrate multi-scale convolutional features in convolutional neural networks (CNNs).

RGB Salient Object Detection Saliency Prediction +1

Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship

no code implementations23 Jan 2019 Jie Liang, Jufeng Yang, Ming-Ming Cheng, Paul L. Rosin, Liang Wang

In this paper we propose a unified framework to simultaneously discover the number of clusters and group the data points into them using subspace clustering.

Model Selection

Salient Object Detection via High-to-Low Hierarchical Context Aggregation

no code implementations28 Dec 2018 Yun Liu, Yu Qiu, Le Zhang, Jia-Wang Bian, Guang-Yu Nie, Ming-Ming Cheng

In this paper, we observe that the contexts of a natural image can be well expressed by a high-to-low self-learning of side-output convolutional features.

RGB Salient Object Detection Saliency Prediction +2

Self-Erasing Network for Integral Object Attention

no code implementations NeurIPS 2018 Qibin Hou, Peng-Tao Jiang, Yunchao Wei, Ming-Ming Cheng

To test the quality of the generated attention maps, we employ the mined object regions as heuristic cues for learning semantic segmentation models.

Semantic Segmentation

Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation

no code implementations ECCV 2018 Ruochen Fan, Qibin Hou, Ming-Ming Cheng, Gang Yu, Ralph R. Martin, Shi-Min Hu

We also combine our method with Mask R-CNN for instance segmentation, and demonstrated for the first time the ability of weakly supervised instance segmentation using only keyword annotations.

graph partitioning Image-level Supervised Instance Segmentation +3

MatchBench: An Evaluation of Feature Matchers

no code implementations7 Aug 2018 Jia-Wang Bian, Ruihan Yang, Yun Liu, Le Zhang, Ming-Ming Cheng, Ian Reid, WenHai Wu

This leads to a critical absence in this field that there is no standard datasets and evaluation metrics to evaluate different feature matchers fairly.

Hifi: Hierarchical feature integration for skeleton detection

no code implementations1 Jul 2018 Kai Zhao, Wei Shen, ShangHua Gao, Dandan Li, Ming-Ming Cheng

In natural images, the scales (thickness) of object skeletons may dramatically vary among objects and object parts.

Object Skeleton Detection

Enhanced-alignment Measure for Binary Foreground Map Evaluation

2 code implementations26 May 2018 Deng-Ping Fan, Cheng Gong, Yang Cao, Bo Ren, Ming-Ming Cheng, Ali Borji

The existing binary foreground map (FM) measures to address various types of errors in either pixel-wise or structural ways.

Learning Pixel-wise Labeling from the Internet without Human Interaction

no code implementations19 May 2018 Yun Liu, Yujun Shi, Jia-Wang Bian, Le Zhang, Ming-Ming Cheng, Jiashi Feng

Collecting sufficient annotated data is very expensive in many applications, especially for pixel-level prediction tasks such as semantic segmentation.

Semantic Segmentation

Optimizing the F-measure for Threshold-free Salient Object Detection

no code implementations ICCV 2019 Kai Zhao, Shang-Hua Gao, Wenguan Wang, Ming-Ming Cheng

By reformulating the standard F-measure we propose the relaxed F-measure which is differentiable w. r. t the posterior and can be easily appended to the back of CNNs as the loss function.

RGB Salient Object Detection Salient Object Detection

Face Sketch Synthesis Style Similarity:A New Structure Co-occurrence Texture Measure

1 code implementation9 Apr 2018 Deng-Ping Fan, Shengchuan Zhang, Yu-Huan Wu, Ming-Ming Cheng, Bo Ren, Rongrong Ji, Paul L. Rosin

However, human perception of the similarity of two sketches will consider both structure and texture as essential factors and is not sensitive to slight ("pixel-level") mismatches.

Face Sketch Synthesis

Semantic Edge Detection with Diverse Deep Supervision

1 code implementation9 Apr 2018 Yun Liu, Ming-Ming Cheng, Deng-Ping Fan, Le Zhang, JiaWang Bian, DaCheng Tao

Semantic edge detection (SED), which aims at jointly extracting edges as well as their category information, has far-reaching applications in domains such as semantic segmentation, object proposal generation, and object recognition.

Edge Detection Object Proposal Generation +2

WebSeg: Learning Semantic Segmentation from Web Searches

no code implementations27 Mar 2018 Qibin Hou, Ming-Ming Cheng, Jiang-Jiang Liu, Philip H. S. Torr

In this paper, we improve semantic segmentation by automatically learning from Flickr images associated with a particular keyword, without relying on any explicit user annotations, thus substantially alleviating the dependence on accurate annotations when compared to previous weakly supervised methods.

Semantic Segmentation

Three Birds One Stone: A General Architecture for Salient Object Segmentation, Edge Detection and Skeleton Extraction

no code implementations27 Mar 2018 Qibin Hou, Jiang-Jiang Liu, Ming-Ming Cheng, Ali Borji, Philip H. S. Torr

Although these tasks are inherently very different, we show that our unified approach performs very well on all of them and works far better than current single-purpose state-of-the-art methods.

Edge Detection Semantic Segmentation

Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground

no code implementations ECCV 2018 Deng-Ping Fan, Ming-Ming Cheng, Jiang-Jiang Liu, Shang-Hua Gao, Qibin Hou, Ali Borji

Our analysis identifies a serious design bias of existing SOD datasets which assumes that each image contains at least one clearly outstanding salient object in low clutter.

RGB Salient Object Detection Salient Object Detection

Review of Visual Saliency Detection with Comprehensive Information

no code implementations9 Mar 2018 Runmin Cong, Jianjun Lei, Huazhu Fu, Ming-Ming Cheng, Weisi Lin, Qingming Huang

With the acquisition technology development, more comprehensive information, such as depth cue, inter-image correspondence, or temporal relationship, is available to extend image saliency detection to RGBD saliency detection, co-saliency detection, or video saliency detection.

Co-Salient Object Detection Video Saliency Detection

Revisiting Video Saliency: A Large-scale Benchmark and a New Model

1 code implementation CVPR 2018 Wenguan Wang, Jianbing Shen, Fang Guo, Ming-Ming Cheng, Ali Borji

Existing video saliency datasets lack variety and generality of common dynamic scenes and fall short in covering challenging situations in unconstrained environments.

Hi-Fi: Hierarchical Feature Integration for Skeleton Detection

no code implementations5 Jan 2018 Kai Zhao, Wei Shen, Shang-Hua Gao, Dandan Li, Ming-Ming Cheng

In natural images, the scales (thickness) of object skeletons may dramatically vary among objects and object parts, making object skeleton detection a challenging problem.

Object Skeleton Detection

S4Net: Single Stage Salient-Instance Segmentation

1 code implementation CVPR 2019 Ruochen Fan, Ming-Ming Cheng, Qibin Hou, Tai-Jiang Mu, Jingdong Wang, Shi-Min Hu

Taking into account the category-independent property of each target, we design a single stage salient instance segmentation framework, with a novel segmentation branch.

Instance Segmentation Semantic Segmentation

Image Matching: An Application-oriented Benchmark

no code implementations12 Sep 2017 Jia-Wang Bian, Le Zhang, Yun Liu, Wen-Yan Lin, Ming-Ming Cheng, Ian D. Reid

To this end, we present a uniform benchmark with novel evaluation metrics and a large-scale dataset for evaluating the overall performance of image matching methods.


Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach

no code implementations CVPR 2017 Yunchao Wei, Jiashi Feng, Xiaodan Liang, Ming-Ming Cheng, Yao Zhao, Shuicheng Yan

We investigate a principle way to progressively mine discriminative object regions using classification networks to address the weakly-supervised semantic segmentation problems.

Classification General Classification +1

Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation

no code implementations7 Dec 2016 Qinbin Hou, Puneet Kumar Dokania, Daniela Massiceti, Yunchao Wei, Ming-Ming Cheng, Philip Torr

We focus on the following three aspects of EM: (i) initialization; (ii) latent posterior estimation (E-step) and (iii) the parameter update (M-step).

Weakly-Supervised Semantic Segmentation

FLIC: Fast Linear Iterative Clustering with Active Search

no code implementations6 Dec 2016 Jia-Xing Zhao, Ren Bo, Qibin Hou, Ming-Ming Cheng, Paul L. Rosin

It also has drawbacks on convergence rate as a result of both the fixed search region and separately doing the assignment step and the update step.

Sequential Optimization for Efficient High-Quality Object Proposal Generation

no code implementations14 Nov 2015 Ziming Zhang, Yun Liu, Xi Chen, Yanjun Zhu, Ming-Ming Cheng, Venkatesh Saligrama, Philip H. S. Torr

We propose a novel object proposal algorithm, BING++, which inherits the virtue of good computational efficiency of BING but significantly improves its proposal localization quality.

Object Proposal Generation

STC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation

1 code implementation10 Sep 2015 Yunchao Wei, Xiaodan Liang, Yunpeng Chen, Xiaohui Shen, Ming-Ming Cheng, Jiashi Feng, Yao Zhao, Shuicheng Yan

Then, a better network called Enhanced-DCNN is learned with supervision from the predicted segmentation masks of simple images based on the Initial-DCNN as well as the image-level annotations.

RGB Salient Object Detection Salient Object Detection +1

Salient Object Detection: A Benchmark

no code implementations5 Jan 2015 Ali Borji, Ming-Ming Cheng, Huaizu Jiang, Jia Li

We extensively compare, qualitatively and quantitatively, 40 state-of-the-art models (28 salient object detection, 10 fixation prediction, 1 objectness, and 1 baseline) over 6 challenging datasets for the purpose of benchmarking salient object detection and segmentation methods.

RGB Salient Object Detection Salient Object Detection

Salient Object Detection: A Survey

no code implementations18 Nov 2014 Ali Borji, Ming-Ming Cheng, Qibin Hou, Huaizu Jiang, Jia Li

Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision.

Object Proposal Generation RGB Salient Object Detection +2

Salient Object Detection: A Discriminative Regional Feature Integration Approach

no code implementations CVPR 2013 Huaizu Jiang, Zejian yuan, Ming-Ming Cheng, Yihong Gong, Nanning Zheng, Jingdong Wang

Our method, which is based on multi-level image segmentation, utilizes the supervised learning approach to map the regional feature vector to a saliency score.

RGB Salient Object Detection Salient Object Detection +1

BING: Binarized Normed Gradients for Objectness Estimation at 300fps

no code implementations CVPR 2014 Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, Philip Torr

Training a generic objectness measure to produce a small set of candidate object windows, has been shown to speed up the classical sliding window object detection paradigm.

Object Detection

Dense Semantic Image Segmentation with Objects and Attributes

no code implementations CVPR 2014 Shuai Zheng, Ming-Ming Cheng, Jonathan Warrell, Paul Sturgess, Vibhav Vineet, Carsten Rother, Philip H. S. Torr

The concepts of objects and attributes are both important for describing images precisely, since verbal descriptions often contain both adjectives and nouns (e. g. "I see a shiny red chair').

Semantic Segmentation

ImageSpirit: Verbal Guided Image Parsing

no code implementations16 Oct 2013 Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin, Jonathan Warrell, Vibhav Vineet, Paul Sturgess, Nigel Crook, Niloy Mitra, Philip Torr

This allows us to formulate the image parsing problem as one of jointly estimating per-pixel object and attribute labels from a set of training images.

Sketch2Photo: Internet Image Montage

no code implementations ACM Transactions on Graphics 2009 Tao Chen, Ming-Ming Cheng, Ping Tan, Ariel Shamir, Shi-Min Hu

The composed picture is generated by seamlessly stitching several photographs in agreement with the sketch and text labels; these are found by searching the Internet.

Image Retrieval

Cannot find the paper you are looking for? You can Submit a new open access paper.