Search Results for author: Errui Ding

Found 135 papers, 66 papers with code

Decoupled Pseudo-labeling for Semi-Supervised Monocular 3D Object Detection

no code implementations26 Mar 2024 Jiacheng Zhang, Jiaming Li, Xiangru Lin, Wei zhang, Xiao Tan, Junyu Han, Errui Ding, Jingdong Wang, Guanbin Li

Additionally, we present a DepthGradient Projection (DGP) module to mitigate optimization conflicts caused by noisy depth supervision of pseudo-labels, effectively decoupling the depth gradient and removing conflicting gradients.

Monocular 3D Object Detection object-detection +1

TexRO: Generating Delicate Textures of 3D Models by Recursive Optimization

no code implementations22 Mar 2024 Jinbo Wu, Xing Liu, Chenming Wu, Xiaobo Gao, Jialun Liu, Xinqi Liu, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang

We propose an optimal viewpoint selection strategy, that finds the most miniature set of viewpoints covering all the faces of a mesh.

Denoising Texture Synthesis

Gradient-based Sampling for Class Imbalanced Semi-supervised Object Detection

1 code implementation ICCV 2023 Jiaming Li, Xiangru Lin, Wei zhang, Xiao Tan, YingYing Li, Junyu Han, Errui Ding, Jingdong Wang, Guanbin Li

To tackle the confirmation bias from incorrect pseudo labels of minority classes, the class-rebalancing sampling module resamples unlabeled data following the guidance of the gradient-based reweighting module.

object-detection Object Detection +1

GGRt: Towards Pose-free Generalizable 3D Gaussian Splatting in Real-time

no code implementations15 Mar 2024 Hao Li, Yuanyuan Gao, Chenming Wu, Dingwen Zhang, Yalun Dai, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang, Junwei Han

Specifically, we design a novel joint learning framework that consists of an Iterative Pose Optimization Network (IPO-Net) and a Generalizable 3D-Gaussians (G-3DG) model.

Generalizable Novel View Synthesis Novel View Synthesis

VRP-SAM: SAM with Visual Reference Prompt

1 code implementation27 Feb 2024 Yanpeng Sun, Jiahui Chen, Shan Zhang, Xinyu Zhang, Qiang Chen, Gang Zhang, Errui Ding, Jingdong Wang, Zechao Li

In this paper, we propose a novel Visual Reference Prompt (VRP) encoder that empowers the Segment Anything Model (SAM) to utilize annotated reference images as prompts for segmentation, creating the VRP-SAM model.

Meta-Learning Segmentation

GVA: Reconstructing Vivid 3D Gaussian Avatars from Monocular Videos

no code implementations26 Feb 2024 Xinqi Liu, Chenming Wu, Jialun Liu, Xing Liu, Jinbo Wu, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang

In this paper, we present a novel method that facilitates the creation of vivid 3D Gaussian avatars from monocular video inputs (GVA).

Novel View Synthesis Pose Estimation

MS-DETR: Efficient DETR Training with Mixed Supervision

1 code implementation8 Jan 2024 Chuyang Zhao, Yifan Sun, Wenhao Wang, Qiang Chen, Errui Ding, Yi Yang, Jingdong Wang

The traditional training procedure using one-to-one supervision in the original DETR lacks direct supervision for the object detection candidates.

Decoder Object +2

Layered Rendering Diffusion Model for Zero-Shot Guided Image Synthesis

1 code implementation30 Nov 2023 Zipeng Qi, Guoxi Huang, Zebin Huang, Qin Guo, Jinwen Chen, Junyu Han, Jian Wang, Gang Zhang, Lufei Liu, Errui Ding, Jingdong Wang

The LRDiff framework constructs an image-rendering process with multiple layers, each of which applies the vision guidance to instructively estimate the denoising direction for a single object.

Denoising Image Generation

HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception

1 code implementation NeurIPS 2023 Junkun Yuan, Xinyu Zhang, Hao Zhou, Jian Wang, Zhongwei Qiu, Zhiyin Shao, Shaofeng Zhang, Sifan Long, Kun Kuang, Kun Yao, Junyu Han, Errui Ding, Lanfen Lin, Fei Wu, Jingdong Wang

To further capture human characteristics, we propose a structure-invariant alignment loss that enforces different masked views, guided by the human part prior, to be closely aligned for the same image.

2D Pose Estimation Attribute +3

Accelerating Vision Transformers Based on Heterogeneous Attention Patterns

no code implementations11 Oct 2023 Deli Yu, Teng Xi, Jianwei Li, Baopu Li, Gang Zhang, Haocheng Feng, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang

On one hand, different images share more similar attention patterns in early layers than later layers, indicating that the dynamic query-by-key self-attention matrix may be replaced with a static self-attention matrix in early layers.

Dimensionality Reduction

Forward Flow for Novel View Synthesis of Dynamic Scenes

no code implementations ICCV 2023 Xiang Guo, Jiadai Sun, Yuchao Dai, GuanYing Chen, Xiaoqing Ye, Xiao Tan, Errui Ding, Yumeng Zhang, Jingdong Wang

This paper proposes a neural radiance field (NeRF) approach for novel view synthesis of dynamic scenes using forward warping.

Novel View Synthesis

VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generation

no code implementations1 Sep 2023 Xin Li, Wenqing Chu, Ye Wu, Weihang Yuan, Fanglong Liu, Qi Zhang, Fu Li, Haocheng Feng, Errui Ding, Jingdong Wang

In this paper, we present VideoGen, a text-to-video generation approach, which can generate a high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion.

Decoder Text-to-Image Generation +2

Group Pose: A Simple Baseline for End-to-End Multi-person Pose Estimation

2 code implementations ICCV 2023 Huan Liu, Qiang Chen, Zichang Tan, Jiang-Jiang Liu, Jian Wang, Xiangbo Su, Xiaolong Li, Kun Yao, Junyu Han, Errui Ding, Yao Zhao, Jingdong Wang

State-of-the-art solutions adopt the DETR-like framework, and mainly develop the complex decoder, e. g., regarding pose estimation as keypoint box detection and combining with human detection in ED-Pose, hierarchically predicting with pose decoder and joint (keypoint) decoder in PETR.

Decoder Human Detection +1

HD-Fusion: Detailed Text-to-3D Generation Leveraging Multiple Noise Estimation

no code implementations30 Jul 2023 Jinbo Wu, Xiaobo Gao, Xing Liu, Zhengyang Shen, Chen Zhao, Haocheng Feng, Jingtuo Liu, Errui Ding

In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models.

3D Generation Noise Estimation +1

Semi-DETR: Semi-Supervised Object Detection with Detection Transformers

3 code implementations CVPR 2023 Jiacheng Zhang, Xiangru Lin, Wei zhang, Kuo Wang, Xiao Tan, Junyu Han, Errui Ding, Jingdong Wang, Guanbin Li

Specifically, we propose a Stage-wise Hybrid Matching strategy that combines the one-to-many assignment and one-to-one assignment strategies to improve the training efficiency of the first stage and thus provide high-quality pseudo labels for the training of the second stage.

Object object-detection +3

Building an Invisible Shield for Your Portrait against Deepfakes

no code implementations22 May 2023 Jiazhi Guan, Tianshu Hu, Hang Zhou, Zhizhi Guo, Lirui Deng, Chengbin Quan, Errui Ding, Youjian Zhao

Unlike authentic images, where the hidden messages can be extracted with precision, manipulating the facial attributes through deepfake techniques can disrupt the decoding process.

Face Swapping

Multi-Modal 3D Object Detection by Box Matching

1 code implementation12 May 2023 Zhe Liu, Xiaoqing Ye, Zhikang Zou, Xinwei He, Xiao Tan, Errui Ding, Jingdong Wang, Xiang Bai

Extensive experiments on the nuScenes dataset demonstrate that our method is much more stable in dealing with challenging cases such as asynchronous sensors, misaligned sensor placement, and degenerated camera images than existing fusion methods.

3D Object Detection Autonomous Driving +2

StyleSync: High-Fidelity Generalized and Personalized Lip Sync in Style-based Generator

no code implementations CVPR 2023 Jiazhi Guan, Zhanwang Zhang, Hang Zhou, Tianshu Hu, Kaisiyuan Wang, Dongliang He, Haocheng Feng, Jingtuo Liu, Errui Ding, Ziwei Liu, Jingdong Wang

Despite recent advances in syncing lip movements with any audio waves, current methods still struggle to balance generation quality and the model's generalization ability.

ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Box

no code implementations27 Mar 2023 Yifu Zhang, Xinggang Wang, Xiaoqing Ye, Wei zhang, Jincheng Lu, Xiao Tan, Errui Ding, Peize Sun, Jingdong Wang

We propose a hierarchical data association strategy to mine the true objects in low-score detection boxes, which alleviates the problems of object missing and fragmented trajectories.

3D Multi-Object Tracking motion prediction +1

Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection

1 code implementation CVPR 2023 Chang Liu, Weiming Zhang, Xiangru Lin, Wei zhang, Xiao Tan, Junyu Han, Xiaomao Li, Errui Ding, Jingdong Wang

It employs a "divide-and-conquer" strategy and separately exploits positives for the classification and localization task, which is more robust to the assignment ambiguity.

Dense Object Detection Object +3

StrucTexTv2: Masked Visual-Textual Prediction for Document Image Pre-training

1 code implementation1 Mar 2023 Yuechen Yu, Yulin Li, Chengquan Zhang, Xiaoqiang Zhang, Zengyuan Guo, Xiameng Qin, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang

Compared to the masked multi-modal modeling methods for document image understanding that rely on both the image and text modalities, StrucTexTv2 models image-only input and potentially deals with more application scenarios free from OCR pre-processing.

Document Image Classification Language Modelling +3

Temporal Segment Transformer for Action Segmentation

no code implementations25 Feb 2023 Zhichao Liu, Leshan Wang, Desen Zhou, Jian Wang, Songyang Zhang, Yang Bai, Errui Ding, Rui Fan

To deal with these issues, we propose an attention based approach which we call \textit{temporal segment transformer}, for joint segment relation modeling and denoising.

Action Segmentation Denoising +1

Graph Contrastive Learning for Skeleton-based Action Recognition

1 code implementation26 Jan 2023 Xiaohu Huang, Hao Zhou, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang, Xinggang Wang, Wenyu Liu, Bin Feng

In this paper, we propose a graph contrastive learning framework for skeleton-based action recognition (\textit{SkeletonGCL}) to explore the \textit{global} context across all sequences.

Action Recognition Contrastive Learning +2

StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection

no code implementations4 Jan 2023 Zhe Liu, Xiaoqing Ye, Xiao Tan, Errui Ding, Xiang Bai

In this paper, we propose a cross-modal distillation method named StereoDistill to narrow the gap between the stereo and LiDAR-based approaches via distilling the stereo detectors from the superior LiDAR model at the response level, which is usually overlooked in 3D object detection distillation.

3D Object Detection object-detection

CFCG: Semi-Supervised Semantic Segmentation via Cross-Fusion and Contour Guidance Supervision

no code implementations ICCV 2023 Shuo Li, Yue He, Weiming Zhang , Wei zhang, Xiao Tan, Junyu Han, Errui Ding, Jingdong Wang

Current state-of-the-art semi-supervised semantic segmentation (SSSS) methods typically adopt pseudo labeling and consistency regularization between multiple learners with different perturbations.

Semi-Supervised Semantic Segmentation

Masked Lip-Sync Prediction by Audio-Visual Contextual Exploitation in Transformers

no code implementations9 Dec 2022 Yasheng Sun, Hang Zhou, Kaisiyuan Wang, Qianyi Wu, Zhibin Hong, Jingtuo Liu, Errui Ding, Jingdong Wang, Ziwei Liu, Hideki Koike

This requires masking a large percentage of the original image and seamlessly inpainting it with the aid of audio and reference frames.

Group DETR v2: Strong Object Detector with Encoder-Decoder Pretraining

no code implementations arXiv 2022 Qiang Chen, Jian Wang, Chuchu Han, Shan Zhang, Zexian Li, Xiaokang Chen, Jiahui Chen, Xiaodi Wang, Shuming Han, Gang Zhang, Haocheng Feng, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang

The training process consists of self-supervised pretraining and finetuning a ViT-Huge encoder on ImageNet-1K, pretraining the detector on Object365, and finally finetuning it on COCO.

Decoder Object +2

U-HRNet: Delving into Improving Semantic Representation of High Resolution Network for Dense Prediction

4 code implementations13 Oct 2022 Jian Wang, Xiang Long, Guowei Chen, Zewu Wu, Zeyu Chen, Errui Ding

Therefore, we designed a U-shaped High-Resolution Network (U-HRNet), which adds more stages after the feature map with strongest semantic representation and relaxes the constraint in HRNet that all resolutions need to be calculated parallel for a newly added stage.

Depth Estimation Depth Prediction +1

Repainting and Imitating Learning for Lane Detection

no code implementations11 Oct 2022 Yue He, Minyue Jiang, Xiaoqing Ye, Liang Du, Zhikang Zou, Wei zhang, Xiao Tan, Errui Ding

In this paper, we target at finding an enhanced feature space where the lane features are distinctive while maintaining a similar distribution of lanes in the wild.

Lane Detection

StyleSwap: Style-Based Generator Empowers Robust Face Swapping

no code implementations27 Sep 2022 Zhiliang Xu, Hang Zhou, Zhibin Hong, Ziwei Liu, Jiaming Liu, Zhizhi Guo, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang

Our core idea is to leverage a style-based generator to empower high-fidelity and robust face swapping, thus the generator's advantage can be adopted for optimizing identity similarity.

Face Swapping

Effective Invertible Arbitrary Image Rescaling

no code implementations26 Sep 2022 Zhihong Pan, Baopu Li, Dongliang He, Wenhao Wu, Errui Ding

To increase its real world applicability, numerous models have also been proposed to restore SR images with arbitrary scale factors, including asymmetric ones where images are resized to different scales along horizontal and vertical directions.

Image Super-Resolution

MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition

no code implementations31 Aug 2022 Yunhao Wang, Huixin Sun, Xiaodi Wang, Bin Zhang, Chao Li, Ying Xin, Baochang Zhang, Errui Ding, Shumin Han

We develop a simple but effective module to explore the full potential of transformers for visual representation by learning fine-grained and coarse-grained features at a token level and dynamically fusing them.

Instance Segmentation object-detection +2

CODER: Coupled Diversity-Sensitive Momentum Contrastive Learning for Image-Text Retrieval

no code implementations21 Aug 2022 Haoran Wang, Dongliang He, Wenhao Wu, Boyang xia, Min Yang, Fu Li, Yunlong Yu, Zhong Ji, Errui Ding, Jingdong Wang

We introduce dynamic dictionaries for both modalities to enlarge the scale of image-text pairs, and diversity-sensitiveness is achieved by adaptive negative pair weighting.

Clustering Contrastive Learning +4

Part-aware Prototypical Graph Network for One-shot Skeleton-based Action Recognition

no code implementations19 Aug 2022 Tailin Chen, Desen Zhou, Jian Wang, Shidong Wang, Qian He, Chuanyang Hu, Errui Ding, Yu Guan, Xuming He

In this paper, we study the problem of one-shot skeleton-based action recognition, which poses unique challenges in learning transferable representation from base classes to novel classes, particularly for fine-grained actions.

Action Recognition Meta-Learning +1

Boosting Video-Text Retrieval with Explicit High-Level Semantics

no code implementations8 Aug 2022 Haoran Wang, Di Xu, Dongliang He, Fu Li, Zhong Ji, Jungong Han, Errui Ding

Video-text retrieval (VTR) is an attractive yet challenging task for multi-modal understanding, which aims to search for relevant video (text) given a query (video).

Retrieval Text Retrieval +3

Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment

2 code implementations ICCV 2023 Qiang Chen, Xiaokang Chen, Jian Wang, Shan Zhang, Kun Yao, Haocheng Feng, Junyu Han, Errui Ding, Gang Zeng, Jingdong Wang

Detection transformer (DETR) relies on one-to-one assignment, assigning one ground-truth object to one prediction, for end-to-end detection without NMS post-processing.

Data Augmentation Decoder +3

Detecting Deepfake by Creating Spatio-Temporal Regularity Disruption

no code implementations21 Jul 2022 Jiazhi Guan, Hang Zhou, Mingming Gong, Errui Ding, Jingdong Wang, Youjian Zhao

Specifically, by carefully examining the spatial and temporal properties, we propose to disrupt a real video through a Pseudo-fake Generator and create a wide range of pseudo-fake videos for training.

DeepFake Detection Face Swapping

Action Quality Assessment with Temporal Parsing Transformer

1 code implementation19 Jul 2022 Yang Bai, Desen Zhou, Songyang Zhang, Jian Wang, Errui Ding, Yu Guan, Yang Long, Jingdong Wang

Action Quality Assessment(AQA) is important for action understanding and resolving the task poses unique challenges due to subtle visual differences.

Action Quality Assessment Action Understanding +2

Neural Color Operators for Sequential Image Retouching

2 code implementations17 Jul 2022 Yili Wang, Xin Li, Kun Xu, Dongliang He, Qi Zhang, Fu Li, Errui Ding

The neural color operator mimics the behavior of traditional color operators and learns pixelwise color transformation while its strength is controlled by a scalar.

Decoder Image Enhancement +1

Paint and Distill: Boosting 3D Object Detection with Semantic Passing Network

no code implementations12 Jul 2022 Bo Ju, Zhikang Zou, Xiaoqing Ye, Minyue Jiang, Xiao Tan, Errui Ding, Jingdong Wang

In this work, we propose a novel semantic passing framework, named SPNet, to boost the performance of existing lidar-based 3D detection models with the guidance of rich context painting, with no extra computation cost during inference.

3D Object Detection Autonomous Driving +1

Delving into Sequential Patches for Deepfake Detection

no code implementations6 Jul 2022 Jiazhi Guan, Hang Zhou, Zhibin Hong, Errui Ding, Jingdong Wang, Chengbin Quan, Youjian Zhao

Recent advances in face forgery techniques produce nearly visually untraceable deepfake videos, which could be leveraged with malicious intentions.

DeepFake Detection Face Swapping

MaskOCR: Text Recognition with Masked Encoder-Decoder Pretraining

no code implementations1 Jun 2022 Pengyuan Lyu, Chengquan Zhang, Shanshan Liu, Meina Qiao, Yangliu Xu, Liang Wu, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang

Specifically, we transform text data into synthesized text images to unify the data modalities of vision and language, and enhance the language modeling capability of the sequence decoder using a proposed masked image-language modeling scheme.

Decoder Language Modelling +2

Few-Shot Font Generation by Learning Fine-Grained Local Styles

2 code implementations CVPR 2022 Licheng Tang, Yiyang Cai, Jiaming Liu, Zhibin Hong, Mingming Gong, Minhu Fan, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang

Instead of explicitly disentangling global or component-wise modeling, the cross-attention mechanism can attend to the right local styles in the reference glyphs and aggregate the reference styles into a fine-grained style representation for the given content glyphs.

Font Generation

Few-Shot Head Swapping in the Wild

no code implementations CVPR 2022 Changyong Shu, Hemao Wu, Hang Zhou, Jiaming Liu, Zhibin Hong, Changxing Ding, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang

Particularly, seamless blending is achieved with the help of a Semantic-Guided Color Reference Creation procedure and a Blending UNet.

Face Swapping

Human-Object Interaction Detection via Disentangled Transformer

no code implementations CVPR 2022 Desen Zhou, Zhichao Liu, Jian Wang, Leshan Wang, Tao Hu, Errui Ding, Jingdong Wang

To associate the predictions of disentangled decoders, we first generate a unified representation for HOI triplets with a base decoder, and then utilize it as input feature of each disentangled decoder.

Decoder Human-Object Interaction Detection +1

GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation

no code implementations16 Apr 2022 Shi Gong, Xiaoqing Ye, Xiao Tan, Jingdong Wang, Errui Ding, Yu Zhou, Xiang Bai

Birds-eye-view (BEV) semantic segmentation is critical for autonomous driving for its powerful spatial representation ability.

Autonomous Driving Image Segmentation +2

Implicit Sample Extension for Unsupervised Person Re-Identification

1 code implementation CVPR 2022 Xinyu Zhang, Dongdong Li, Zhigang Wang, Jian Wang, Errui Ding, Javen Qinfeng Shi, Zhaoxiang Zhang, Jingdong Wang

Specifically, we generate support samples from actual samples and their neighbouring clusters in the embedding space through a progressive linear interpolation (PLI) strategy.

Clustering Unsupervised Person Re-Identification

ViSTA: Vision and Scene Text Aggregation for Cross-Modal Retrieval

no code implementations CVPR 2022 Mengjun Cheng, Yipeng Sun, Longchao Wang, Xiongwei Zhu, Kun Yao, Jie Chen, Guoli Song, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang

Visual appearance is considered to be the most important cue to understand images for cross-modal retrieval, while sometimes the scene text appearing in images can provide valuable information to understand the visual semantics.

Ranked #10 on Cross-Modal Retrieval on Flickr30k (using extra training data)

Contrastive Learning Cross-Modal Retrieval +1

Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task

no code implementations25 Mar 2022 Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding

On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.

Autonomous Driving Monocular 3D Object Detection +1

Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence

no code implementations CVPR 2022 Zhihong Pan, Baopu Li, Dongliang He, Mingde Yao, Wenhao Wu, Tianwei Lin, Xin Li, Errui Ding

Deep learning based single image super-resolution models have been widely studied and superb results are achieved in upscaling low-resolution images with fixed scale factor and downscaling degradation kernel.

Image Super-Resolution

MobileFaceSwap: A Lightweight Framework for Video Face Swapping

1 code implementation11 Jan 2022 Zhiliang Xu, Zhibin Hong, Changxing Ding, Zhen Zhu, Junyu Han, Jingtuo Liu, Errui Ding

In this work, we propose a lightweight Identity-aware Dynamic Network (IDN) for subject-agnostic face swapping by dynamically adjusting the model parameters according to the identity information.

Face Swapping Knowledge Distillation

Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task

no code implementations CVPR 2022 Xiaoqing Ye, Mao Shu, Hanyu Li, Yifeng Shi, YingYing Li, Guangjie Wang, Xiao Tan, Errui Ding

On the other hand, the data captured from roadside cameras have strengths over frontal-view data, which is believed to facilitate a safer and more intelligent autonomous driving system.

Autonomous Driving Monocular 3D Object Detection +1

Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model

1 code implementation CVPR 2022 Zipeng Xu, Tianwei Lin, Hao Tang, Fu Li, Dongliang He, Nicu Sebe, Radu Timofte, Luc van Gool, Errui Ding

We propose a novel framework, i. e., Predict, Prevent, and Evaluate (PPE), for disentangled text-driven image manipulation that requires little manual annotation while being applicable to a wide variety of manipulations.

Image Manipulation Language Modelling

An Information Theory-inspired Strategy for Automatic Network Pruning

1 code implementation19 Aug 2021 Xiawu Zheng, Yuexiao Ma, Teng Xi, Gang Zhang, Errui Ding, Yuchao Li, Jie Chen, Yonghong Tian, Rongrong Ji

This practically limits the application of model compression when the model needs to be deployed on a wide range of devices.

AutoML Model Compression +1

Learning Multi-Granular Spatio-Temporal Graph Network for Skeleton-based Action Recognition

1 code implementation10 Aug 2021 Tailin Chen, Desen Zhou, Jian Wang, Shidong Wang, Yu Guan, Xuming He, Errui Ding

The task of skeleton-based action recognition remains a core challenge in human-centred scene understanding due to the multiple granularities and large variation in human motion.

Action Classification Action Recognition +2

Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video

no code implementations9 Aug 2021 Jie Wu, Wei zhang, Guanbin Li, Wenhao Wu, Xiao Tan, YingYing Li, Errui Ding, Liang Lin

In this paper, we introduce a novel task, referred to as Weakly-Supervised Spatio-Temporal Anomaly Detection (WSSTAD) in surveillance video.

Anomaly Detection

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction

2 code implementations ICCV 2021 Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Ruifeng Deng, Xin Li, Errui Ding, Hao Wang

Neural painting refers to the procedure of producing a series of strokes for a given image and non-photo-realistically recreating it using neural networks.

Object Detection Reinforcement Learning (RL) +1

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

3 code implementations ICCV 2021 Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Meiling Wang, Xin Li, Zhengxing Sun, Qian Li, Errui Ding

Finally, the content feature is normalized so that they demonstrate the same local feature statistics as the calculated per-point weighted style feature statistics.

Style Transfer Video Style Transfer

Oriented Object Detection with Transformer

no code implementations6 Jun 2021 Teli Ma, Mingyuan Mao, Honghui Zheng, Peng Gao, Xiaodi Wang, Shumin Han, Errui Ding, Baochang Zhang, David Doermann

Object detection with Transformers (DETR) has achieved a competitive performance over traditional detectors, such as Faster R-CNN.

Object object-detection +2

Dual-stream Network for Visual Recognition

no code implementations NeurIPS 2021 Mingyuan Mao, Renrui Zhang, Honghui Zheng, Peng Gao, Teli Ma, Yan Peng, Errui Ding, Baochang Zhang, Shumin Han

Transformers with remarkable global representation capacities achieve competitive results for visual tasks, but fail to consider high-level local pattern information in input images.

Image Classification Instance Segmentation +3

Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness

1 code implementation28 Apr 2021 Manyu Zhu, Dongliang He, Xin Li, Chao Li, Fu Li, Xiao Liu, Errui Ding, Zhaoxiang Zhang

Inpainting arbitrary missing regions is challenging because learning valid features for various masked regions is nontrivial.

Decoder Image Inpainting +1

PAFNet: An Efficient Anchor-Free Object Detector Guidance

1 code implementation28 Apr 2021 Ying Xin, Guanzhong Wang, Mingyuan Mao, Yuan Feng, Qingqing Dang, Yanjun Ma, Errui Ding, Shumin Han

Therefore, a trade-off between effectiveness and efficiency is necessary in practical scenarios.

 Ranked #1 on Object Detection on COCO test-dev (Hardware Burden metric)

Object object-detection +1

Unsupervised Multi-Source Domain Adaptation for Person Re-Identification

1 code implementation CVPR 2021 Zechen Bai, Zhigang Wang, Jian Wang, Di Hu, Errui Ding

Although achieving great success, most of them only use limited data from a single-source domain for model pre-training, making the rich labeled data insufficiently exploited.

Person Re-Identification Unsupervised Domain Adaptation

Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer

2 code implementations CVPR 2021 Tianwei Lin, Zhuoqi Ma, Fu Li, Dongliang He, Xin Li, Errui Ding, Nannan Wang, Jie Li, Xinbo Gao

Inspired by the common painting process of drawing a draft and revising the details, we introduce a novel feed-forward method named Laplacian Pyramid Network (LapStyle).

Style Transfer

PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network

2 code implementations12 Apr 2021 Pengfei Wang, Chengquan Zhang, Fei Qi, Shanshan Liu, Xiaoqiang Zhang, Pengyuan Lyu, Junyu Han, Jingtuo Liu, Errui Ding, Guangming Shi

With a PG-CTC decoder, we gather high-level character classification vectors from two-dimensional space and decode them into text symbols without NMS and RoI operations involved, which guarantees high efficiency.

 Ranked #1 on Scene Text Detection on ICDAR 2015 (Accuracy metric)

Decoder Optical Character Recognition (OCR) +2

Student-Teacher Feature Pyramid Matching for Anomaly Detection

10 code implementations7 Mar 2021 Guodong Wang, Shumin Han, Errui Ding, Di Huang

Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies.

Image Classification Unsupervised Anomaly Detection

FaceController: Controllable Attribute Editing for Face in the Wild

no code implementations23 Feb 2021 Zhiliang Xu, Xiyu Yu, Zhibin Hong, Zhen Zhu, Junyu Han, Jingtuo Liu, Errui Ding, Xiang Bai

By simply employing some existing and easy-obtainable prior information, our method can control, transfer, and edit diverse attributes of faces in the wild.

 Ranked #1 on Face Swapping on FaceForensics++ (FID metric)

Attribute Disentanglement +1

Revealing the Reciprocal Relations Between Self-Supervised Stereo and Monocular Depth Estimation

no code implementations ICCV 2021 Zhi Chen, Xiaoqing Ye, Wei Yang, Zhenbo Xu, Xiao Tan, Zhikang Zou, Errui Ding, Xinming Zhang, Liusheng Huang

Second, we introduce an occlusion-aware distillation (OA Distillation) module, which leverages the predicted depths from StereoNet in non-occluded regions to train our monocular depth estimation network named SingleNet.

Monocular Depth Estimation Stereo Matching

EC-DARTS: Inducing Equalized and Consistent Optimization Into DARTS

no code implementations ICCV 2021 Qinqin Zhou, Xiawu Zheng, Liujuan Cao, Bineng Zhong, Teng Xi, Gang Zhang, Errui Ding, Mingliang Xu, Rongrong Ji

EC-DARTS decouples different operations based on their categories to optimize the operation weights so that the operation gap between them is shrinked.

Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective

1 code implementation14 Dec 2020 Xuanmeng Zhang, Minyue Jiang, Zhedong Zheng, Xiao Tan, Errui Ding, Yi Yang

We argue that the first phase equals building the k-nearest neighbor graph, while the second phase can be viewed as spreading the message within the graph.

Drone-view target localization Image Retrieval +4

MVFNet: Multi-View Fusion Network for Efficient Video Recognition

3 code implementations13 Dec 2020 Wenhao Wu, Dongliang He, Tianwei Lin, Fu Li, Chuang Gan, Errui Ding

Existing state-of-the-art methods have achieved excellent accuracy regardless of the complexity meanwhile efficient spatiotemporal modeling solutions are slightly inferior in performance.

Action Classification Action Recognition +2

Coherent Loss: A Generic Framework for Stable Video Segmentation

no code implementations25 Oct 2020 Mingyang Qian, Yi Fu, Xiao Tan, YingYing Li, Jinqing Qi, Huchuan Lu, Shilei Wen, Errui Ding

Video segmentation approaches are of great importance for numerous vision tasks especially in video manipulation for entertainment.

Segmentation Semantic Segmentation +2

HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network

2 code implementations15 Oct 2020 Pengcheng Yuan, Shufei Lin, Cheng Cui, Yuning Du, Ruoyu Guo, Dongliang He, Errui Ding, Shumin Han

Moreover, Hierarchical-Split block is very flexible and efficient, which provides a large space of potential network architectures for different applications.

Image Classification Image Segmentation +5

Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matching

1 code implementation NeurIPS 2020 Di Hu, Rui Qian, Minyue Jiang, Xiao Tan, Shilei Wen, Errui Ding, Weiyao Lin, Dejing Dou

First, we propose to learn robust object representations by aggregating the candidate sound localization results in the single source scenes.

Object Object Localization

Real Image Super Resolution Via Heterogeneous Model Ensemble using GP-NAS

no code implementations2 Sep 2020 Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding

With advancement in deep neural network (DNN), recent state-of-the-art (SOTA) image superresolution (SR) methods have achieved impressive performance using deep residual network with dense skip connections.

Image Super-Resolution Neural Architecture Search

Learning Global Structure Consistency for Robust Object Tracking

no code implementations26 Aug 2020 Bi Li, Chengquan Zhang, Zhibin Hong, Xu Tang, Jingtuo Liu, Junyu Han, Errui Ding, Wenyu Liu

Unlike many existing trackers that focus on modeling only the target, in this work, we consider the \emph{transient variations of the whole scene}.

Object Visual Object Tracking

PP-YOLO: An Effective and Efficient Implementation of Object Detector

5 code implementations23 Jul 2020 Xiang Long, Kaipeng Deng, Guanzhong Wang, Yang Zhang, Qingqing Dang, Yuan Gao, Hui Shen, Jianguo Ren, Shumin Han, Errui Ding, Shilei Wen

We mainly try to combine various existing tricks that almost not increase the number of model parameters and FLOPs, to achieve the goal of improving the accuracy of detector as much as possible while ensuring that the speed is almost unchanged.

Ranked #134 on Object Detection on COCO test-dev (using extra training data)

Object object-detection +1

Graph-PCNN: Two Stage Human Pose Estimation with Graph Pose Refinement

no code implementations ECCV 2020 Jian Wang, Xiang Long, Yuan Gao, Errui Ding, Shilei Wen

In the first stage, heatmap regression network is applied to obtain a rough localization result, and a set of proposal keypoints, called guided points, are sampled.

Pose Estimation regression +1

PointTrack++ for Effective Online Multi-Object Tracking and Segmentation

1 code implementation3 Jul 2020 Zhenbo Xu, Wei zhang, Xiao Tan, Wei Yang, Xiangbo Su, Yuchen Yuan, Hongwu Zhang, Shilei Wen, Errui Ding, Liusheng Huang

In this work, we present PointTrack++, an effective on-line framework for MOTS, which remarkably extends our recently proposed PointTrack framework.

Data Augmentation Decoder +8

Segment as Points for Efficient Online Multi-Object Tracking and Segmentation

1 code implementation ECCV 2020 Zhenbo Xu, Wei zhang, Xiao Tan, Wei Yang, Huan Huang, Shilei Wen, Errui Ding, Liusheng Huang

The resulting online MOTS framework, named PointTrack, surpasses all the state-of-the-art methods including 3D tracking methods by large margins (5. 4% higher MOTSA and 18 times faster over MOTSFusion) with the near real-time speed (22 FPS).

Multi-Object Tracking Multi-Object Tracking and Segmentation +1

Learning Generalized Spoof Cues for Face Anti-spoofing

6 code implementations8 May 2020 Haocheng Feng, Zhibin Hong, Haixiao Yue, Yang Chen, Keyao Wang, Junyu Han, Jingtuo Liu, Errui Ding

In this paper, we reformulate FAS in an anomaly detection perspective and propose a residual-learning framework to learn the discriminative live-spoof differences which are defined as the spoof cues.

Anomaly Detection Face Anti-Spoofing

ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection

1 code implementation1 Mar 2020 Zhenbo Xu, Wei zhang, Xiaoqing Ye, Xiao Tan, Wei Yang, Shilei Wen, Errui Ding, Ajin Meng, Liusheng Huang

The pipeline of ZoomNet begins with an ordinary 2D object detection model which is used to obtain pairs of left-right bounding boxes.

3D Object Detection Autonomous Driving +2

HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer Faces

no code implementations19 Dec 2019 Yang Liu, Xu Tang, Xiang Wu, Junyu Han, Jingtuo Liu, Errui Ding

In this paper, we propose an Online High-quality Anchor Mining Strategy (HAMBox), which explicitly helps outer faces compensate with high-quality anchors.

Face Detection Multi-Task Learning +2

Dynamic Instance Normalization for Arbitrary Style Transfer

no code implementations16 Nov 2019 Yongcheng Jing, Xiao Liu, Yukang Ding, Xinchao Wang, Errui Ding, Mingli Song, Shilei Wen

Prior normalization methods rely on affine transformations to produce arbitrary image style transfers, of which the parameters are computed in a pre-defined way.

Style Transfer

ACFNet: Attentional Class Feature Network for Semantic Segmentation

1 code implementation ICCV 2019 Fan Zhang, Yanqin Chen, Zhihang Li, Zhibin Hong, Jingtuo Liu, Feifei Ma, Junyu Han, Errui Ding

Recent works have made great progress in semantic segmentation by exploiting richer context, most of which are designed from a spatial perspective.

Segmentation Semantic Segmentation

EATEN: Entity-aware Attention for Single Shot Visual Text Extraction

1 code implementation20 Sep 2019 He guo, Xiameng Qin, Jiaming Liu, Junyu Han, Jingtuo Liu, Errui Ding

Extracting entity from images is a crucial part of many OCR applications, such as entity recognition of cards, invoices, and receipts.

Decoder Entity Extraction using GAN +1

Chinese Street View Text: Large-scale Chinese Text Reading with Partially Supervised Learning

no code implementations ICCV 2019 Yipeng Sun, Jiaming Liu, Wei Liu, Junyu Han, Errui Ding, Jingtuo Liu

Most existing text reading benchmarks make it difficult to evaluate the performance of more advanced deep learning models in large vocabularies due to the limited amount of training data.

Perspective-Guided Convolution Networks for Crowd Counting

1 code implementation ICCV 2019 Zhaoyi Yan, Yuchen Yuan, WangMeng Zuo, Xiao Tan, Yezhen Wang, Shilei Wen, Errui Ding

In this paper, we propose a novel perspective-guided convolution (PGC) for convolutional neural network (CNN) based crowd counting (i. e. PGCNet), which aims to overcome the dramatic intra-scene scale variations of people due to the perspective effect.

Crowd Counting

ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT)

1 code implementation16 Sep 2019 Chee-Kheng Chng, Yuliang Liu, Yipeng Sun, Chun Chet Ng, Canjie Luo, Zihan Ni, ChuanMing Fang, Shuaitao Zhang, Junyu Han, Errui Ding, Jingtuo Liu, Dimosthenis Karatzas, Chee Seng Chan, Lianwen Jin

This paper reports the ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text (RRC-ArT) that consists of three major challenges: i) scene text detection, ii) scene text recognition, and iii) scene text spotting.

Scene Text Detection Scene Text Recognition +2

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.

Decoder Image Inpainting +1

An End-to-end Video Text Detector with Online Tracking

no code implementations20 Aug 2019 Hongyuan Yu, Chengquan Zhang, Xuan Li, Junyu Han, Errui Ding, Liang Wang

Most existing methods attempt to enhance the performance of video text detection by cooperating with video text tracking, but treat these two tasks separately.

Text Detection

Editing Text in the Wild

2 code implementations8 Aug 2019 Liang Wu, Chengquan Zhang, Jiaming Liu, Junyu Han, Jingtuo Liu, Errui Ding, Xiang Bai

Specifically, we propose an end-to-end trainable style retention network (SRNet) that consists of three modules: text conversion module, background inpainting module and fusion module.

Image Inpainting Image-to-Image Translation +1

BMN: Boundary-Matching Network for Temporal Action Proposal Generation

15 code implementations ICCV 2019 Tianwei Lin, Xiao Liu, Xin Li, Errui Ding, Shilei Wen

To address these difficulties, we introduce the Boundary-Matching (BM) mechanism to evaluate confidence scores of densely distributed proposals, which denote a proposal as a matching pair of starting and ending boundaries and combine all densely distributed BM pairs into the BM confidence map.

Action Detection Action Recognition +1

Detecting Text in the Wild with Deep Character Embedding Network

no code implementations2 Jan 2019 Jiaming Liu, Chengquan Zhang, Yipeng Sun, Junyu Han, Errui Ding

However, text in the wild is usually perspectively distorted or curved, which can not be easily tackled by existing approaches.

Clustering Text Detection

TextNet: Irregular Text Reading from Images with an End-to-End Trainable Network

no code implementations24 Dec 2018 Yipeng Sun, Chengquan Zhang, Zuming Huang, Jiaming Liu, Junyu Han, Errui Ding

Reading text from images remains challenging due to multi-orientation, perspective distortion and especially the curved nature of irregular text.

Optical Character Recognition (OCR) Text Detection

Compact Generalized Non-local Network

2 code implementations NeurIPS 2018 Kaiyu Yue, Ming Sun, Yuchen Yuan, Feng Zhou, Errui Ding, Fuxin Xu

The non-local module is designed for capturing long-range spatio-temporal dependencies in images and videos.

Object Detection Object Recognition +1

Fine-grained Video Categorization with Redundancy Reduction Attention

no code implementations ECCV 2018 Chen Zhu, Xiao Tan, Feng Zhou, Xiao Liu, Kaiyu Yue, Errui Ding, Yi Ma

Specifically, it firstly summarizes the video by weight-summing all feature vectors in the feature maps of selected frames with a spatio-temporal soft attention, and then predicts which channels to suppress or to enhance according to this summary with a learned non-linear transform.

Action Recognition Video Classification

Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition

1 code implementation ECCV 2018 Ming Sun, Yuchen Yuan, Feng Zhou, Errui Ding

Attention-based learning for fine-grained image recognition remains a challenging task, where most of the existing methods treat each object part in isolation, while neglecting the correlations among them.

Fine-Grained Image Recognition Metric Learning

WordSup: Exploiting Word Annotations for Character based Text Detection

no code implementations ICCV 2017 Han Hu, Chengquan Zhang, Yuxuan Luo, Yuzhuo Wang, Junyu Han, Errui Ding

When applied in scene text detection, we are thus able to train a robust character detector by exploiting word annotations in the rich large-scale real scene text datasets, e. g. ICDAR15 and COCO-text.

Math Scene Text Detection +1

Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition

no code implementations20 May 2016 Xiao Liu, Jiang Wang, Shilei Wen, Errui Ding, Yuanqing Lin

By designing a novel reward strategy, we are able to learn to locate regions that are spatially and semantically distinctive with reinforcement learning algorithm.

Attribute reinforcement-learning +1

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