Search Results for author: Chongyang Zhang

Found 16 papers, 4 papers with code

Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection

no code implementations20 Mar 2024 Xincheng Yao, Ruoqi Li, Zefeng Qian, Lu Wang, Chongyang Zhang

In this paper, we propose a novel Hierarchical Gaussian mixture normalizing flow modeling method for accomplishing unified Anomaly Detection, which we call HGAD.

Anomaly Detection

Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection

1 code implementation ICCV 2023 Xincheng Yao, Ruoqi Li, Zefeng Qian, Yan Luo, Chongyang Zhang

Humans recognize anomalies through two aspects: larger patch-wise representation discrepancies and weaker patch-to-normal-patch correlations.

Anomaly Detection Self-Supervised Learning

Towards Diverse Temporal Grounding under Single Positive Labels

1 code implementation12 Mar 2023 Hao Zhou, Chongyang Zhang, Yanjun Chen, Chuanping Hu

In this study, we reformulate this task as a one-vs-many optimization problem under the condition of single positive labels.

Moment Retrieval Retrieval

Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection

1 code implementation CVPR 2023 Xincheng Yao, Ruoqi Li, Jing Zhang, Jun Sun, Chongyang Zhang

In this way, our model can form a more explicit and discriminative decision boundary to distinguish known and also unseen anomalies from normal samples more effectively.

Ranked #3 on Supervised Anomaly Detection on MVTec AD (using extra training data)

Contrastive Learning Supervised Anomaly Detection

Embracing Uncertainty: Decoupling and De-bias for Robust Temporal Grounding

no code implementations CVPR 2021 Hao Zhou, Chongyang Zhang, Yan Luo, Yanjun Chen, Chuanping Hu

Meanwhile, modified feature assigned with style-like words (including adjectives, adverbs, etc) represents the subjective information, and thus brings personalized predictions; De-bias - We propose a de-bias mechanism to generate diverse predictions, aim to alleviate the bias caused by single-style annotations in the presence of label uncertainty.

Relation

Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection

no code implementations18 Mar 2021 Yan Luo, Chongyang Zhang, Muming Zhao, Hao Zhou, Jun Sun

Consequently, we address the weakness of IoU by introducing one geometric sensitive search algorithm as a new assignment and regression metric.

Autonomous Driving Pedestrian Detection +1

Where, What, Whether: Multi-modal Learning Meets Pedestrian Detection

no code implementations CVPR 2020 Yan Luo, Chongyang Zhang, Muming Zhao, Hao Zhou, Jun Sun

i) We generate a bird view map, which is naturally free from occlusion issues, and scan all points on it to look for suitable locations for each pedestrian instance.

Pedestrian Detection

Visual Relationship Detection with Relative Location Mining

1 code implementation2 Nov 2019 Hao Zhou, Chongyang Zhang, Chuanping Hu

Visual relationship detection, as a challenging task used to find and distinguish the interactions between object pairs in one image, has received much attention recently.

Object Relationship Detection +1

Towards Locally Consistent Object Counting with Constrained Multi-stage Convolutional Neural Networks

no code implementations6 Apr 2019 Muming Zhao, Jian Zhang, Chongyang Zhang, Wenjun Zhang

Towards this problem, in this paper we propose a constrained multi-stage Convolutional Neural Networks (CNNs) to jointly pursue locally consistent density map from two aspects.

Object Object Counting

Image Segmentation Based on Multiscale Fast Spectral Clustering

no code implementations12 Dec 2018 Chongyang Zhang, Guofeng Zhu, Minxin Chen, Hong Chen, Chenjian Wu

The computational complexity of Multiscale Fast Spectral Clustering is O(nlogn) and its memory cost is O(m).

Clustering Image Segmentation +3

Enhancing HEVC Compressed Videos with a Partition-masked Convolutional Neural Network

no code implementations10 May 2018 Xiaoyi He, Qiang Hu, Xintong Han, Xiaoyun Zhang, Chongyang Zhang, Weiyao Lin

In this paper, we propose a partition-masked Convolution Neural Network (CNN) to achieve compressed-video enhancement for the state-of-the-art coding standard, High Efficiency Video Coding (HECV).

Multimedia

Tree-based Visualization and Optimization for Image Collection

no code implementations17 Jul 2015 Xintong Han, Chongyang Zhang, Weiyao Lin, Mingliang Xu, Bin Sheng, Tao Mei

The visualization of an image collection is the process of displaying a collection of images on a screen under some specific layout requirements.

Long-Term Correlation Tracking

no code implementations CVPR 2015 Chao Ma, Xiaokang Yang, Chongyang Zhang, Ming-Hsuan Yang

In this paper, we address the problem of long-term visual tracking where the target objects undergo significant appearance variation due to deformation, abrupt motion, heavy occlusion and out-of-the-view.

Translation Visual Tracking

Intra-and-Inter-Constraint-based Video Enhancement based on Piecewise Tone Mapping

no code implementations21 Feb 2015 Yuanzhe Chen, Weiyao Lin, Chongyang Zhang, Zhenzhong Chen, Ning Xu, Jun Xie

In this paper, we propose a new intra-and-inter-constraint-based video enhancement approach aiming to 1) achieve high intra-frame quality of the entire picture where multiple region-of-interests (ROIs) can be adaptively and simultaneously enhanced, and 2) guarantee the inter-frame quality consistencies among video frames.

Tone Mapping Video Enhancement

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