Search Results for author: Li Niu

Found 76 papers, 47 papers with code

Shadow Generation for Composite Image Using Diffusion model

1 code implementation22 Mar 2024 Qingyang Liu, Junqi You, Jianting Wang, Xinhao Tao, Bo Zhang, Li Niu

In the realm of image composition, generating realistic shadow for the inserted foreground remains a formidable challenge.

Image-to-Image Translation

Meta-Point Learning and Refining for Category-Agnostic Pose Estimation

1 code implementation20 Mar 2024 Junjie Chen, Jiebin Yan, Yuming Fang, Li Niu

Existing methods only rely on the features extracted at support keypoints to predict or refine the keypoints on query image, but a few support feature vectors are local and inadequate for CAPE.

Category-Agnostic Pose Estimation Decoder +1

A Single Simple Patch is All You Need for AI-generated Image Detection

no code implementations2 Feb 2024 Jiaxuan Chen, Jieteng Yao, Li Niu

The recent development of generative models unleashes the potential of generating hyper-realistic fake images.

Painterly Image Harmonization by Learning from Painterly Objects

1 code implementation15 Dec 2023 Li Niu, Junyan Cao, Yan Hong, Liqing Zhang

In particular, we learn a mapping from background style and object information to object style based on painterly objects in artistic paintings.

Image Harmonization Object

Progressive Painterly Image Harmonization from Low-level Styles to High-level Styles

1 code implementation15 Dec 2023 Li Niu, Yan Hong, Junyan Cao, Liqing Zhang

Painterly image harmonization aims to harmonize a photographic foreground object on the painterly background.

Image Harmonization

Painterly Image Harmonization via Adversarial Residual Learning

no code implementations15 Nov 2023 Xudong Wang, Li Niu, Junyan Cao, Yan Hong, Liqing Zhang

In this work, we employ adversarial learning to bridge the domain gap between foreground feature map and background feature map.

Image Harmonization

Virtual Accessory Try-On via Keypoint Hallucination

no code implementations26 Oct 2023 Junhong Gou, Bo Zhang, Li Niu, Jianfu Zhang, Jianlou Si, Chen Qian, Liqing Zhang

Specifically, our approach learns the human body priors and hallucinates the target locations of specified foreground keypoints in the background.

Hallucination Semantic Segmentation +1

DreamCom: Finetuning Text-guided Inpainting Model for Image Composition

no code implementations27 Sep 2023 Lingxiao Lu, Jiangtong Li, Bo Zhang, Li Niu

The goal of image composition is merging a foreground object into a background image to obtain a realistic composite image.

Image Inpainting Object +1

DESOBAv2: Towards Large-scale Real-world Dataset for Shadow Generation

1 code implementation19 Aug 2023 Qingyang Liu, Jianting Wang, Li Niu

In this work, we focus on generating plausible shadow for the inserted foreground object to make the composite image more realistic.

Object Shadow Detection

ControlCom: Controllable Image Composition using Diffusion Model

1 code implementation19 Aug 2023 Bo Zhang, Yuxuan Duan, Jun Lan, Yan Hong, Huijia Zhu, Weiqiang Wang, Li Niu

To address these challenges, we propose a controllable image composition method that unifies four tasks in one diffusion model: image blending, image harmonization, view synthesis, and generative composition.

Image Harmonization

Foreground Object Search by Distilling Composite Image Feature

1 code implementation ICCV 2023 Bo Zhang, Jiacheng Sui, Li Niu

Additionally, previous works did not release their datasets, so we contribute two datasets for FOS task: S-FOSD dataset with synthetic composite images and R-FOSD dataset with real composite images.

Object Retrieval

Deep Image Harmonization in Dual Color Spaces

1 code implementation5 Aug 2023 Linfeng Tan, Jiangtong Li, Li Niu, Liqing Zhang

The network comprises a $RGB$ harmonization backbone, an $Lab$ encoding module, and an $Lab$ control module.

Decoder Image Harmonization

Painterly Image Harmonization using Diffusion Model

1 code implementation4 Aug 2023 Lingxiao Lu, Jiangtong Li, Junyan Cao, Li Niu, Liqing Zhang

Painterly image harmonization aims to insert photographic objects into paintings and obtain artistically coherent composite images.

Generative Adversarial Network Image Harmonization +1

Scene-aware Human Pose Generation using Transformer

no code implementations4 Aug 2023 Jieteng Yao, Junjie Chen, Li Niu, Bin Sheng

Affordance learning considers the interaction opportunities for an actor in the scene and thus has wide application in scene understanding and intelligent robotics.

Knowledge Distillation Scene Understanding

Deep Image Harmonization with Learnable Augmentation

1 code implementation ICCV 2023 Li Niu, Junyan Cao, Wenyan Cong, Liqing Zhang

In particular, our designed SYthetic COmposite Network (SycoNet) takes in a real image with foreground mask and a random vector to learn suitable color transformation, which is applied to the foreground of this real image to produce a synthetic composite image.

Image Harmonization

Shadow Generation with Decomposed Mask Prediction and Attentive Shadow Filling

1 code implementation30 Jun 2023 Xinhao Tao, Junyan Cao, Yan Hong, Li Niu

Specifically, in the first stage, we decompose shadow mask prediction into box prediction and shape prediction.

Object

WeditGAN: Few-Shot Image Generation via Latent Space Relocation

1 code implementation11 May 2023 Yuxuan Duan, Li Niu, Yan Hong, Liqing Zhang

In this work, we introduce WeditGAN, which realizes model transfer by editing the intermediate latent codes $w$ in StyleGANs with learned constant offsets ($\Delta w$), discovering and constructing target latent spaces via simply relocating the distribution of source latent spaces.

Image Generation

Image Cropping With Spatial-Aware Feature and Rank Consistency

no code implementations CVPR 2023 Chao Wang, Li Niu, Bo Zhang, Liqing Zhang

To address the first issue, we propose spatial-aware feature to encode the spatial relationship between candidate crops and aesthetic elements, by feeding the concatenation of crop mask and selectively aggregated feature maps to a light-weighted encoder.

Image Cropping

Fine-grained Visible Watermark Removal

no code implementations ICCV 2023 Li Niu, Xing Zhao, Bo Zhang, Liqing Zhang

Visible watermark removal aims to erase the watermark from watermarked image and recover the background image, which is a challenging task due to the diverse watermarks.

Knowledge Proxy Intervention for Deconfounded Video Question Answering

no code implementations ICCV 2023 Jiangtong Li, Li Niu, Liqing Zhang

To tackle the challenge that the confounder in VideoQA is unobserved and non-enumerable in general, we propose a model-agnostic framework called Knowledge Proxy Intervention (KPI), which introduces an extra knowledge proxy variable in the causal graph to cut the backdoor path and remove the confounder.

Question Answering Video Question Answering

Painterly Image Harmonization in Dual Domains

1 code implementation17 Dec 2022 Junyan Cao, Yan Hong, Li Niu

In this work, we propose a novel painterly harmonization network consisting of a dual-domain generator and a dual-domain discriminator, which harmonizes the composite image in both spatial domain and frequency domain.

Image Harmonization

Video Object of Interest Segmentation

no code implementations6 Dec 2022 Siyuan Zhou, Chunru Zhan, Biao Wang, Tiezheng Ge, Yuning Jiang, Li Niu

Given a video and a target image of interest, our objective is to simultaneously segment and track all objects in the video that are relevant to the target image.

Decoder Object +4

Inharmonious Region Localization via Recurrent Self-Reasoning

no code implementations5 Oct 2022 Penghao Wu, Li Niu, Jing Liang, Liqing Zhang

Synthetic images created by image editing operations are prevalent, but the color or illumination inconsistency between the manipulated region and background may make it unrealistic.

Clustering Decoder +1

Inharmonious Region Localization with Auxiliary Style Feature

no code implementations5 Oct 2022 Penghao Wu, Li Niu, Liqing Zhang

Based on the extracted style features, we also propose a novel style voting module to guide the localization of inharmonious region.

Weak-shot Semantic Segmentation via Dual Similarity Transfer

1 code implementation5 Oct 2022 Junjie Chen, Li Niu, Siyuan Zhou, Jianlou Si, Chen Qian, Liqing Zhang

Proposal segmentation allows proposal-pixel similarity transfer from base classes to novel classes, which enables the mask learning of novel classes.

Segmentation Semantic Segmentation +2

Inharmonious Region Localization by Magnifying Domain Discrepancy

1 code implementation30 Sep 2022 Jing Liang, Li Niu, Penghao Wu, Fengjun Guo, Teng Long

Inharmonious region localization aims to localize the region in a synthetic image which is incompatible with surrounding background.

Image Harmonization

Learning Object Placement via Dual-path Graph Completion

1 code implementation23 Jul 2022 Siyuan Zhou, Liu Liu, Li Niu, Liqing Zhang

Object placement aims to place a foreground object over a background image with a suitable location and size.

Object

DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta

1 code implementation21 Jul 2022 Yan Hong, Li Niu, Jianfu Zhang, Liqing Zhang

In this work, we propose a novel Delta Generative Adversarial Network (DeltaGAN), which consists of a reconstruction subnetwork and a generation subnetwork.

Generative Adversarial Network Image Generation

Human-centric Image Cropping with Partition-aware and Content-preserving Features

1 code implementation21 Jul 2022 Bo Zhang, Li Niu, Xing Zhao, Liqing Zhang

Image cropping aims to find visually appealing crops in an image, which is an important yet challenging task.

Image Cropping

Spatial Transformation for Image Composition via Correspondence Learning

no code implementations6 Jul 2022 Bo Zhang, Yue Liu, Kaixin Lu, Li Niu, Liqing Zhang

Instead, we propose a novel correspondence learning network (CorrelNet) to model the correspondence between foreground and background using cross-attention maps, based on which we can predict the target coordinate that each source coordinate of foreground should be mapped to on the background.

Virtual Try-on

CcHarmony: Color-checker based Image Harmonization Dataset

1 code implementation1 Jun 2022 Haoxu Huang, Li Niu

Image harmonization targets at adjusting the foreground in a composite image to make it compatible with the background, producing a more realistic and harmonious image.

Image Harmonization

Fast Object Placement Assessment

1 code implementation28 May 2022 Li Niu, Qingyang Liu, Zhenchen Liu, Jiangtong Li

However, given a pair of scaled foreground and background, to enumerate all the reasonable locations, existing OPA model needs to place the foreground at each location on the background and pass the obtained composite image through the model one at a time, which is very time-consuming.

Object

Deep Video Harmonization with Color Mapping Consistency

1 code implementation2 May 2022 Xinyuan Lu, Shengyuan Huang, Li Niu, Wenyan Cong, Liqing Zhang

Video harmonization aims to adjust the foreground of a composite video to make it compatible with the background.

Video Harmonization

Dual-Path Image Inpainting With Auxiliary GAN Inversion

no code implementations CVPR 2022 Wentao Wang, Li Niu, Jianfu Zhang, Xue Yang, Liqing Zhang

Different from feed-forward methods, they seek for a closest latent code to the corrupted image and feed it to a pretrained generator.

Image Inpainting

Mixed Supervised Object Detection by Transferring Mask Prior and Semantic Similarity

1 code implementation NeurIPS 2021 Yan Liu, Zhijie Zhang, Li Niu, Junjie Chen, Liqing Zhang

Specifically, the ability of using mask prior to help detect objects is learned from base categories and transferred to novel categories.

Object object-detection +3

Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary

no code implementations4 Oct 2021 Siyuan Zhou, Li Niu, Jianlou Si, Chen Qian, Liqing Zhang

As a result, we find that pixel-level annotation of base categories can facilitate affinity learning and propagation, leading to higher-quality CAMs of novel categories.

Segmentation Weakly supervised Semantic Segmentation +1

HYouTube: Video Harmonization Dataset

1 code implementation18 Sep 2021 Xinyuan Lu, Shengyuan Huang, Li Niu, Wenyan Cong, Liqing Zhang

In this work, we construct a new video harmonization dataset HYouTube by adjusting the foreground of real videos to create synthetic composite videos.

Video Harmonization

High-Resolution Image Harmonization via Collaborative Dual Transformations

1 code implementation CVPR 2022 Wenyan Cong, Xinhao Tao, Li Niu, Jing Liang, Xuesong Gao, Qihao Sun, Liqing Zhang

Conventional image harmonization methods learn global RGB-to-RGB transformation which could effortlessly scale to high resolution, but ignore diverse local context.

Image Harmonization Vocal Bursts Intensity Prediction

Visible Watermark Removal via Self-calibrated Localization and Background Refinement

1 code implementation8 Aug 2021 Jing Liang, Li Niu, Fengjun Guo, Teng Long, Liqing Zhang

In the refinement stage, we integrate multi-level features to improve the texture quality of watermarked area.

Multi-Task Learning

OPA: Object Placement Assessment Dataset

3 code implementations5 Jul 2021 Liu Liu, Zhenchen Liu, Bo Zhang, Jiangtong Li, Li Niu, Qingyang Liu, Liqing Zhang

Image composition aims to generate realistic composite image by inserting an object from one image into another background image, where the placement (e. g., location, size, occlusion) of inserted object may be unreasonable, which would significantly degrade the quality of the composite image.

Object

Making Images Real Again: A Comprehensive Survey on Deep Image Composition

4 code implementations28 Jun 2021 Li Niu, Wenyan Cong, Liu Liu, Yan Hong, Bo Zhang, Jing Liang, Liqing Zhang

We have also contributed the first image composition toolbox: libcom https://github. com/bcmi/libcom, which assembles 10+ image composition related functions (e. g., image blending, image harmonization, object placement, shadow generation, generative composition).

Image Harmonization

End-to-End Video Object Detection with Spatial-Temporal Transformers

1 code implementation23 May 2021 Lu He, Qianyu Zhou, Xiangtai Li, Li Niu, Guangliang Cheng, Xiao Li, Wenxuan Liu, Yunhai Tong, Lizhuang Ma, Liqing Zhang

Recently, DETR and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance as previous complex hand-crafted detectors.

Object object-detection +2

Shadow Generation for Composite Image in Real-world Scenes

1 code implementation21 Apr 2021 Yan Hong, Li Niu, Jianfu Zhang, Liqing Zhang

In this work, we focus on generating plausible shadow for the foreground object in the composite image.

Object

Inharmonious Region Localization

1 code implementation19 Apr 2021 Jing Liang, Li Niu, Liqing Zhang

The advance of image editing techniques allows users to create artistic works, but the manipulated regions may be incompatible with the background.

Decoder Image Harmonization

Image Composition Assessment with Saliency-augmented Multi-pattern Pooling

1 code implementation7 Apr 2021 Bo Zhang, Li Niu, Liqing Zhang

Image composition assessment is crucial in aesthetic assessment, which aims to assess the overall composition quality of a given image.

Aesthetics Quality Assessment

Deep Image Harmonization by Bridging the Reality Gap

1 code implementation31 Mar 2021 Junyan Cao, Wenyan Cong, Li Niu, Jianfu Zhang, Liqing Zhang

Image harmonization has been significantly advanced with large-scale harmonization dataset.

Image Harmonization Transfer Learning

Parallel Multi-Resolution Fusion Network for Image Inpainting

no code implementations ICCV 2021 Wentao Wang, Jianfu Zhang, Li Niu, Haoyu Ling, Xue Yang, Liqing Zhang

Conventional deep image inpainting methods are based on auto-encoder architecture, in which the spatial details of images will be lost in the down-sampling process, leading to the degradation of generated results.

Image Inpainting

Disentangled Information Bottleneck

1 code implementation14 Dec 2020 Ziqi Pan, Li Niu, Jianfu Zhang, Liqing Zhang

The information bottleneck (IB) method is a technique for extracting information that is relevant for predicting the target random variable from the source random variable, which is typically implemented by optimizing the IB Lagrangian that balances the compression and prediction terms.

Adversarial Attack Out-of-Distribution Detection

From Pixel to Patch: Synthesize Context-aware Features for Zero-shot Semantic Segmentation

1 code implementation25 Sep 2020 Zhangxuan Gu, Siyuan Zhou, Li Niu, Zihan Zhao, Liqing Zhang

Thus, we focus on zero-shot semantic segmentation, which aims to segment unseen objects with only category-level semantic representations provided for unseen categories.

Image Classification Segmentation +3

BargainNet: Background-Guided Domain Translation for Image Harmonization

1 code implementation19 Sep 2020 Wenyan Cong, Li Niu, Jianfu Zhang, Jing Liang, Liqing Zhang

Therefore, we propose an image harmonization network with a novel domain code extractor and well-tailored triplet losses, which could capture the background domain information to guide the foreground harmonization.

Image Harmonization Translation

Weak-shot Fine-grained Classification via Similarity Transfer

1 code implementation NeurIPS 2021 Junjie Chen, Li Niu, Liu Liu, Liqing Zhang

In this setting, we propose a method called SimTrans to transfer pairwise semantic similarity from base categories to novel categories.

Classification General Classification +2

DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta

1 code implementation18 Sep 2020 Yan Hong, Li Niu, Jianfu Zhang, Jing Liang, Liqing Zhang

In this work, we propose a novel Delta Generative Adversarial Network (DeltaGAN), which consists of a reconstruction subnetwork and a generation subnetwork.

Generative Adversarial Network Image Generation

Context-aware Feature Generation for Zero-shot Semantic Segmentation

2 code implementations16 Aug 2020 Zhangxuan Gu, Siyuan Zhou, Li Niu, Zihan Zhao, Liqing Zhang

In this paper, we propose a novel context-aware feature generation method for zero-shot segmentation named CaGNet.

Segmentation Semantic Segmentation +3

F2GAN: Fusing-and-Filling GAN for Few-shot Image Generation

1 code implementation5 Aug 2020 Yan Hong, Li Niu, Jianfu Zhang, Weijie Zhao, Chen Fu, Liqing Zhang

In this paper, we propose a Fusing-and-Filling Generative Adversarial Network (F2GAN) to generate realistic and diverse images for a new category with only a few images.

Generative Adversarial Network Image Generation

Beyond without Forgetting: Multi-Task Learning for Classification with Disjoint Datasets

no code implementations15 Mar 2020 Yan Hong, Li Niu, Jianfu Zhang, Liqing Zhang

To address these issues, we propose our MTL with Selective Augmentation (MTL-SA) method to select the training samples in unlabeled datasets with confident pseudo labels and close data distribution to the labeled dataset.

General Classification Multi-Task Learning

MatchingGAN: Matching-based Few-shot Image Generation

1 code implementation7 Mar 2020 Yan Hong, Li Niu, Jianfu Zhang, Liqing Zhang

Matching generator can match random vectors with a few conditional images from the same category and generate new images for this category based on the fused features.

Generative Adversarial Network Image Generation

Exploiting Motion Information from Unlabeled Videos for Static Image Action Recognition

no code implementations1 Dec 2019 Yiyi Zhang, Li Niu, Ziqi Pan, Meichao Luo, Jianfu Zhang, Dawei Cheng, Liqing Zhang

Specifically, the VRE module includes a proxy task which imposes pseudo motion label constraint and temporal coherence constraint on unlabeled videos, while the MRA module could predict the motion information of a static action image by exploiting unlabeled videos.

Action Recognition Self-Supervised Learning

Zero-Shot Sketch-Based Image Retrieval with Structure-aware Asymmetric Disentanglement

no code implementations29 Nov 2019 Jiangtong Li, Zhixin Ling, Li Niu, Liqing Zhang

The goal of Sketch-Based Image Retrieval (SBIR) is using free-hand sketches to retrieve images of the same category from a natural image gallery.

Disentanglement Retrieval +2

DoveNet: Deep Image Harmonization via Domain Verification

1 code implementation CVPR 2020 Wenyan Cong, Jianfu Zhang, Li Niu, Liu Liu, Zhixin Ling, Weiyuan Li, Liqing Zhang

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image.

Image Harmonization

Image Cropping with Composition and Saliency Aware Aesthetic Score Map

no code implementations24 Nov 2019 Yi Tu, Li Niu, Weijie Zhao, Dawei Cheng, Liqing Zhang

Aesthetic image cropping is a practical but challenging task which aims at finding the best crops with the highest aesthetic quality in an image.

Image Cropping

A Proposal-based Approach for Activity Image-to-Video Retrieval

no code implementations24 Nov 2019 Ruicong Xu, Li Niu, Jianfu Zhang, Liqing Zhang

Activity image-to-video retrieval task aims to retrieve videos containing the similar activity as the query image, which is a challenging task because videos generally have many background segments irrelevant to the activity.

Cross-Modal Retrieval Retrieval +1

Image Harmonization Dataset iHarmony4: HCOCO, HAdobe5k, HFlickr, and Hday2night

1 code implementation28 Aug 2019 Wenyan Cong, Jianfu Zhang, Li Niu, Liu Liu, Zhixin Ling, Weiyuan Li, Liqing Zhang

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image.

Image Harmonization

Learning from Web Data with Self-Organizing Memory Module

no code implementations CVPR 2020 Yi Tu, Li Niu, Junjie Chen, Dawei Cheng, Liqing Zhang

However, crawled web images usually have two types of noises, label noise and background noise, which induce extra difficulties in utilizing them effectively.

Image Classification

Hard Pixel Mining for Depth Privileged Semantic Segmentation

1 code implementation27 Jun 2019 Zhangxuan Gu, Li Niu, Haohua Zhao, Liqing Zhang

Specifically, we propose a novel Loss Weight Module, which outputs a loss weight map by employing two depth-related measurements of hard pixels: Depth Prediction Error and Depthaware Segmentation Error.

Depth Estimation Depth Prediction +2

Fine-grained Classification using Heterogeneous Web Data and Auxiliary Categories

no code implementations19 Nov 2018 Li Niu, Ashok Veeraraghavan, Ashu Sabharwal

In the extreme case, given a set of test categories without any well-labeled training data, the majority of existing works can be grouped into the following two research directions: 1) crawl noisy labeled web data for the test categories as training data, which is dubbed as webly supervised learning; 2) transfer the knowledge from auxiliary categories with well-labeled training data to the test categories, which corresponds to zero-shot learning setting.

Classification General Classification +2

Webly Supervised Learning Meets Zero-Shot Learning: A Hybrid Approach for Fine-Grained Classification

no code implementations CVPR 2018 Li Niu, Ashok Veeraraghavan, Ashutosh Sabharwal

The drawbacks of the above two directions motivate us to design a new framework which can jointly leverage both web data and auxiliary labeled categories to predict the test categories that are not associated with any well-labeled training images.

Fine-Grained Image Classification General Classification +1

Learning from Noisy Web Data with Category-level Supervision

no code implementations CVPR 2018 Li Niu, Qingtao Tang, Ashok Veeraraghavan, Ashu Sabharwal

As tons of photos are being uploaded to public websites (e. g., Flickr, Bing, and Google) every day, learning from web data has become an increasingly popular research direction because of freely available web resources, which is also referred to as webly supervised learning.

General Classification

Zero-Shot Learning via Category-Specific Visual-Semantic Mapping

no code implementations16 Nov 2017 Li Niu, Jianfei Cai, Ashok Veeraraghavan

Zero-Shot Learning (ZSL) aims to classify a test instance from an unseen category based on the training instances from seen categories, in which the gap between seen categories and unseen categories is generally bridged via visual-semantic mapping between the low-level visual feature space and the intermediate semantic space.

General Classification Image Classification +1

Multi-View Domain Generalization for Visual Recognition

no code implementations ICCV 2015 Li Niu, Wen Li, Dong Xu

Considering the recent works show the domain generalization capability can be enhanced by fusing multiple SVM classifiers, we build upon exemplar SVMs to learn a set of SVM classifiers by using one positive sample and all negative samples in the source domain each time.

Domain Generalization

Visual Recognition by Learning From Web Data: A Weakly Supervised Domain Generalization Approach

no code implementations CVPR 2015 Li Niu, Wen Li, Dong Xu

In this work, we formulate a new weakly supervised domain generalization problem for the visual recognition task by using loosely labeled web images/videos as training data.

Domain Generalization

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