Search Results for author: Changqian Yu

Found 17 papers, 13 papers with code

Conditional Boundary Loss for Semantic Segmentation

1 code implementation IEEE Transactions on Image Processing 2023 Dongyue Wu, Zilin Guo, Aoyan Li, Changqian Yu, Nong Sang, Changxin Gao

We conduct extensive experiments on ADE20K, Cityscapes, and Pascal Context, and the results show that applying the CBL to various popular segmentation networks can significantly improve the mIoU and boundary F-score performance.

Segmentation Semantic Segmentation

PLIP: Language-Image Pre-training for Person Representation Learning

1 code implementation15 May 2023 Jialong Zuo, Changqian Yu, Nong Sang, Changxin Gao

Extensive experiments demonstrate that our model not only significantly improves existing methods on all these tasks, but also shows great ability in the few-shot and domain generalization settings.

Pedestrian Attribute Recognition Person Re-Identification +3

Semantic Segmentation via Pixel-to-Center Similarity Calculation

no code implementations12 Jan 2023 Dongyue Wu, Zilin Guo, Aoyan Li, Changqian Yu, Changxin Gao, Nong Sang

Under this novel view, we propose a Class Center Similarity layer (CCS layer) to address the above-mentioned challenges by generating adaptive class centers conditioned on different scenes and supervising the similarities between class centers.

Segmentation Semantic Segmentation

GANet: Goal Area Network for Motion Forecasting

1 code implementation20 Sep 2022 Mingkun Wang, Xinge Zhu, Changqian Yu, Wei Li, Yuexin Ma, Ruochun Jin, Xiaoguang Ren, Dongchun Ren, Mingxu Wang, Wenjing Yang

In view of this, we propose a new goal area-based framework, named Goal Area Network (GANet), for motion forecasting, which models goal areas rather than exact goal coordinates as preconditions for trajectory prediction, performing more robustly and accurately.

Motion Forecasting Trajectory Prediction

CORE: Consistent Representation Learning for Face Forgery Detection

1 code implementation6 Jun 2022 Yunsheng Ni, Depu Meng, Changqian Yu, Chengbin Quan, Dongchun Ren, Youjian Zhao

Specifically, we first capture the different representations with different augmentations, then regularize the cosine distance of the representations to enhance the consistency.

Representation Learning

Attribute-specific Control Units in StyleGAN for Fine-grained Image Manipulation

1 code implementation25 Nov 2021 Rui Wang, Jian Chen, Gang Yu, Li Sun, Changqian Yu, Changxin Gao, Nong Sang

Image manipulation with StyleGAN has been an increasing concern in recent years. Recent works have achieved tremendous success in analyzing several semantic latent spaces to edit the attributes of the generated images. However, due to the limited semantic and spatial manipulation precision in these latent spaces, the existing endeavors are defeated in fine-grained StyleGAN image manipulation, i. e., local attribute translation. To address this issue, we discover attribute-specific control units, which consist of multiple channels of feature maps and modulation styles.

Image Manipulation

CondNet: Conditional Classifier for Scene Segmentation

2 code implementations21 Sep 2021 Changqian Yu, Yuanjie Shao, Changxin Gao, Nong Sang

The last layer of FCN is typically a global classifier (1x1 convolution) to recognize each pixel to a semantic label.

Scene Segmentation Segmentation

Representative Graph Neural Network

no code implementations ECCV 2020 Changqian Yu, Yifan Liu, Changxin Gao, Chunhua Shen, Nong Sang

In this paper, we present a Representative Graph (RepGraph) layer to dynamically sample a few representative features, which dramatically reduces redundancy.

object-detection Object Detection +1

BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation

7 code implementations5 Apr 2020 Changqian Yu, Changxin Gao, Jingbo Wang, Gang Yu, Chunhua Shen, Nong Sang

We propose to treat these spatial details and categorical semantics separately to achieve high accuracy and high efficiency for realtime semantic segmentation.

Real-Time Semantic Segmentation Segmentation

Context Prior for Scene Segmentation

2 code implementations CVPR 2020 Changqian Yu, Jingbo Wang, Changxin Gao, Gang Yu, Chunhua Shen, Nong Sang

Given an input image and corresponding ground truth, Affinity Loss constructs an ideal affinity map to supervise the learning of Context Prior.

Scene Segmentation Scene Understanding +1

Efficient Semantic Video Segmentation with Per-frame Inference

1 code implementation ECCV 2020 Yifan Liu, Chunhua Shen, Changqian Yu, Jingdong Wang

For semantic segmentation, most existing real-time deep models trained with each frame independently may produce inconsistent results for a video sequence.

Knowledge Distillation Optical Flow Estimation +4

GTNet: Generative Transfer Network for Zero-Shot Object Detection

1 code implementation19 Jan 2020 Shizhen Zhao, Changxin Gao, Yuanjie Shao, Lerenhan Li, Changqian Yu, Zhong Ji, Nong Sang

FFU and BFU add the IoU variance to the results of CFU, yielding class-specific foreground and background features, respectively.

object-detection Transfer Learning +1

An End-to-End Network for Panoptic Segmentation

no code implementations CVPR 2019 Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, Wei Jiang

Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic.

Panoptic Segmentation Segmentation

Learning a Discriminative Feature Network for Semantic Segmentation

3 code implementations CVPR 2018 Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang

Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction.

Semantic Segmentation Thermal Image Segmentation

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