Search Results for author: Zhe Lin

Found 106 papers, 41 papers with code

Pushing Paraphrase Away from Original Sentence: A Multi-Round Paraphrase Generation Approach

1 code implementation4 Sep 2021 Zhe Lin, Xiaojun Wan

Both automatic and human evaluation show BTmPG can improve the diversity of paraphrase while preserving the semantics of the original sentence.

Paraphrase Generation Translation

SSH: A Self-Supervised Framework for Image Harmonization

1 code implementation ICCV 2021 Yifan Jiang, He Zhang, Jianming Zhang, Yilin Wang, Zhe Lin, Kalyan Sunkavalli, Simon Chen, Sohrab Amirghodsi, Sarah Kong, Zhangyang Wang

Image harmonization aims to improve the quality of image compositing by matching the "appearance" (\eg, color tone, brightness and contrast) between foreground and background images.

Data Augmentation

Open-World Entity Segmentation

2 code implementations29 Jul 2021 Lu Qi, Jason Kuen, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Zhe Lin, Philip Torr, Jiaya Jia

We introduce a new image segmentation task, termed Entity Segmentation (ES) with the aim to segment all visual entities in an image without considering semantic category labels.

Image Manipulation Semantic Segmentation

Learning to Predict Visual Attributes in the Wild

no code implementations CVPR 2021 Khoi Pham, Kushal Kafle, Zhe Lin, Zhihong Ding, Scott Cohen, Quan Tran, Abhinav Shrivastava

In this paper, we introduce a large-scale in-the-wild visual attribute prediction dataset consisting of over 927K attribute annotations for over 260K object instances.

Contrastive Learning Multi-Label Classification

Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing

1 code implementation9 Jun 2021 Yitao Cai, Zhe Lin, Xiaojun Wan

We argue that the misprediction of concepts is due to the high relevance between English tokens and AMR concepts.

AMR Parsing

Multimodal Contrastive Training for Visual Representation Learning

no code implementations CVPR 2021 Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, Yilin Wang, Michael Maire, Ajinkya Kale, Baldo Faieta

We first train our model on COCO and evaluate the learned visual representations on various downstream tasks including image classification, object detection, and instance segmentation.

Cross-Modal Retrieval Image Classification +4

Content-Aware GAN Compression

1 code implementation CVPR 2021 Yuchen Liu, Zhixin Shu, Yijun Li, Zhe Lin, Federico Perazzi, S. Y. Kung

We then propose a novel content-aware method to guide the processes of both pruning and distillation.

Image Generation Image Manipulation +1

Going Deeper Into Face Detection: A Survey

no code implementations27 Mar 2021 Shervin Minaee, Ping Luo, Zhe Lin, Kevin Bowyer

In this work, we provide a detailed overview of some of the most representative deep learning based face detection methods by grouping them into a few major categories, and present their core architectural designs and accuracies on popular benchmarks.

Face Detection Image Classification

Language-Guided Global Image Editing via Cross-Modal Cyclic Mechanism

no code implementations ICCV 2021 Wentao Jiang, Ning Xu, Jiayun Wang, Chen Gao, Jing Shi, Zhe Lin, Si Liu

Given the cycle, we propose several free augmentation strategies to help our model understand various editing requests given the imbalanced dataset.

Face Image Retrieval With Attribute Manipulation

no code implementations ICCV 2021 Alireza Zaeemzadeh, Shabnam Ghadar, Baldo Faieta, Zhe Lin, Nazanin Rahnavard, Mubarak Shah, Ratheesh Kalarot

For example, a user can ask for retrieving images similar to a query image, but with a different hair color, and no preference for absence/presence of eyeglasses in the results.

Face Image Retrieval

CR-Fill: Generative Image Inpainting With Auxiliary Contextual Reconstruction

1 code implementation ICCV 2021 Yu Zeng, Zhe Lin, Huchuan Lu, Vishal M. Patel

The auxiliary branch (i. e. CR loss) is required only during training, and only the inpainting generator is required during the inference.

Image Inpainting

Semantic Layout Manipulation with High-Resolution Sparse Attention

no code implementations14 Dec 2020 Haitian Zheng, Zhe Lin, Jingwan Lu, Scott Cohen, Jianming Zhang, Ning Xu, Jiebo Luo

A core problem of this task is how to transfer visual details from the input images to the new semantic layout while making the resulting image visually realistic.

Meticulous Object Segmentation

1 code implementation13 Dec 2020 Chenglin Yang, Yilin Wang, Jianming Zhang, He Zhang, Zhe Lin, Alan Yuille

To evaluate segmentation quality near object boundaries, we propose the Meticulosity Quality (MQ) score considering both the mask coverage and boundary precision.

Semantic Segmentation

Mask Guided Matting via Progressive Refinement Network

1 code implementation CVPR 2021 Qihang Yu, Jianming Zhang, He Zhang, Yilin Wang, Zhe Lin, Ning Xu, Yutong Bai, Alan Yuille

We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance.

Hard-ODT: Hardware-Friendly Online Decision Tree Learning Algorithm and System

no code implementations11 Dec 2020 Zhe Lin, Sharad Sinha, Wei zhang

Following this, we present Hard-ODT, a high-performance, hardware-efficient and scalable online decision tree learning system on a field-programmable gate array (FPGA) with system-level optimization techniques.

On the Helpfulness of Document Context to Sentence Simplification

no code implementations COLING 2020 Renliang Sun, Zhe Lin, Xiaojun Wan

Our model uses neural networks to learn the different effects of the preceding sentences and the following sentences on the current sentence and applies them to the improved transformer model.

Text Simplification

CR-Fill: Generative Image Inpainting with Auxiliary Contexutal Reconstruction

1 code implementation25 Nov 2020 Yu Zeng, Zhe Lin, Huchuan Lu, Vishal M. Patel

Due to the lack of supervision signals for the correspondence between missing regions and known regions, it may fail to find proper reference features, which often leads to artifacts in the results.

Image Inpainting

Deep Image Compositing

no code implementations4 Nov 2020 He Zhang, Jianming Zhang, Federico Perazzi, Zhe Lin, Vishal M. Patel

In this paper, we propose a new method which can automatically generate high-quality image compositing without any user input.

Decision Tree Based Hardware Power Monitoring for Run Time Dynamic Power Management in FPGA

no code implementations3 Sep 2020 Zhe Lin, Wei zhang, Sharad Sinha

A flexible architecture of the hardware power monitoring is proposed, which can be instrumented in any RTL design for runtime power estimation, dispensing with the need for extra power measurement devices.

Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGA

no code implementations3 Sep 2020 Zhe Lin, Sharad Sinha, Wei zhang

We further present a high-performance, hardware-efficient and scalable online decision tree learning system on a field-programmable gate array (FPGA) with system-level optimization techniques.

An Ensemble Learning Approach for In-situ Monitoring of FPGA Dynamic Power

no code implementations3 Sep 2020 Zhe Lin, Sharad Sinha, Wei zhang

As field-programmable gate arrays become prevalent in critical application domains, their power consumption is of high concern.

Ensemble Learning

Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions

1 code implementation ECCV 2020 Xihui Liu, Zhe Lin, Jianming Zhang, Handong Zhao, Quan Tran, Xiaogang Wang, Hongsheng Li

We propose a novel algorithm, named Open-Edit, which is the first attempt on open-domain image manipulation with open-vocabulary instructions.

Image Manipulation

PhraseCut: Language-based Image Segmentation in the Wild

1 code implementation CVPR 2020 Chenyun Wu, Zhe Lin, Scott Cohen, Trung Bui, Subhransu Maji

We consider the problem of segmenting image regions given a natural language phrase, and study it on a novel dataset of 77, 262 images and 345, 486 phrase-region pairs.

Referring Expression Segmentation Semantic Segmentation

Shape Adaptor: A Learnable Resizing Module

1 code implementation ECCV 2020 Shikun Liu, Zhe Lin, Yilin Wang, Jianming Zhang, Federico Perazzi, Edward Johns

We present a novel resizing module for neural networks: shape adaptor, a drop-in enhancement built on top of traditional resizing layers, such as pooling, bilinear sampling, and strided convolution.

Image Classification Neural Architecture Search +1

Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation

no code implementations ECCV 2020 Kenan E. Ak, Ning Xu, Zhe Lin, Yilin Wang

To our best knowledge, the proposed method is first to enable adversarial learning in autoregressive models for image generation.

Image Generation

Real-time Semantic Segmentation with Fast Attention

1 code implementation7 Jul 2020 Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko, Stan Sclaroff

The proposed architecture relies on our fast spatial attention, which is a simple yet efficient modification of the popular self-attention mechanism and captures the same rich spatial context at a small fraction of the computational cost, by changing the order of operations.

Real-Time Semantic Segmentation

Context-Aware Group Captioning via Self-Attention and Contrastive Features

no code implementations CVPR 2020 Zhuowan Li, Quan Tran, Long Mai, Zhe Lin, Alan Yuille

In this paper, we introduce a new task, context-aware group captioning, which aims to describe a group of target images in the context of another group of related reference images.

Image Captioning

Scaling Object Detection by Transferring Classification Weights

1 code implementation ICCV 2019 Jason Kuen, Federico Perazzi, Zhe Lin, Jianming Zhang, Yap-Peng Tan

Large scale object detection datasets are constantly increasing their size in terms of the number of classes and annotations count.

Classification General Classification +1

Towards High-Resolution Salient Object Detection

1 code implementation ICCV 2019 Yi Zeng, Pingping Zhang, Jianming Zhang, Zhe Lin, Huchuan Lu

This paper pushes forward high-resolution saliency detection, and contributes a new dataset, named High-Resolution Salient Object Detection (HRSOD).

RGB Salient Object Detection Saliency Detection +1

Expressing Visual Relationships via Language

1 code implementation ACL 2019 Hao Tan, Franck Dernoncourt, Zhe Lin, Trung Bui, Mohit Bansal

To push forward the research in this direction, we first introduce a new language-guided image editing dataset that contains a large number of real image pairs with corresponding editing instructions.

Image Captioning

Multitask Text-to-Visual Embedding with Titles and Clickthrough Data

no code implementations30 May 2019 Pranav Aggarwal, Zhe Lin, Baldo Faieta, Saeid Motiian

In this paper, we propose a new method for learning text-visual embedding using both image titles and click-through data from an image search engine.

Image Retrieval

Multimodal Style Transfer via Graph Cuts

2 code implementations ICCV 2019 Yulun Zhang, Chen Fang, Yilin Wang, Zhaowen Wang, Zhe Lin, Yun Fu, Jimei Yang

An assumption widely used in recent neural style transfer methods is that image styles can be described by global statics of deep features like Gram or covariance matrices.

Style Transfer

Scene Graph Generation with External Knowledge and Image Reconstruction

no code implementations CVPR 2019 Jiuxiang Gu, Handong Zhao, Zhe Lin, Sheng Li, Jianfei Cai, Mingyang Ling

Scene graph generation has received growing attention with the advancements in image understanding tasks such as object detection, attributes and relationship prediction,~\etc.

Graph Generation Image Reconstruction +3

Image Super-Resolution by Neural Texture Transfer

2 code implementations CVPR 2019 Zhifei Zhang, Zhaowen Wang, Zhe Lin, Hairong Qi

Reference-based super-resolution (RefSR), on the other hand, has proven to be promising in recovering high-resolution (HR) details when a reference (Ref) image with similar content as that of the LR input is given.

Image Stylization Image Super-Resolution

Foreground-aware Image Inpainting

no code implementations CVPR 2019 Wei Xiong, Jiahui Yu, Zhe Lin, Jimei Yang, Xin Lu, Connelly Barnes, Jiebo Luo

We show that by such disentanglement, the contour completion model predicts reasonable contours of objects, and further substantially improves the performance of image inpainting.

Image Inpainting

Photo-Sketching: Inferring Contour Drawings from Images

2 code implementations2 Jan 2019 Mengtian Li, Zhe Lin, Radomir Mech, Ersin Yumer, Deva Ramanan

Edges, boundaries and contours are important subjects of study in both computer graphics and computer vision.

Boundary Detection BSDS500

Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization

1 code implementation CVPR 2019 Siyuan Qiao, Zhe Lin, Jianming Zhang, Alan Yuille

By simply replacing standard optimizers with Neural Rejuvenation, we are able to improve the performances of neural networks by a very large margin while using similar training efforts and maintaining their original resource usages.

Network Pruning Neural Architecture Search

Sequence-to-Segment Networks for Segment Detection

no code implementations NeurIPS 2018 Zijun Wei, Boyu Wang, Minh Hoai Nguyen, Jianming Zhang, Zhe Lin, Xiaohui Shen, Radomir Mech, Dimitris Samaras

Detecting segments of interest from an input sequence is a challenging problem which often requires not only good knowledge of individual target segments, but also contextual understanding of the entire input sequence and the relationships between the target segments.

Temporal Action Proposal Generation Video Summarization

Spatial-temporal Multi-Task Learning for Within-field Cotton Yield Prediction

no code implementations16 Nov 2018 Long Nguyen, Jia Zhen, Zhe Lin, Hanxiang Du, Zhou Yang, Wenxuan Guo, Fang Jin

Understanding and accurately predicting within-field spatial variability of crop yield play a key role in site-specific management of crop inputs such as irrigation water and fertilizer for optimized crop production.

Crop Yield Prediction Multi-Task Learning

DeepLens: Shallow Depth Of Field From A Single Image

no code implementations18 Oct 2018 Lijun Wang, Xiaohui Shen, Jianming Zhang, Oliver Wang, Zhe Lin, Chih-Yao Hsieh, Sarah Kong, Huchuan Lu

To achieve this, we propose a novel neural network model comprised of a depth prediction module, a lens blur module, and a guided upsampling module.

Depth Estimation

GAPLE: Generalizable Approaching Policy LEarning for Robotic Object Searching in Indoor Environment

no code implementations21 Sep 2018 Xin Ye, Zhe Lin, Joon-Young Lee, Jianming Zhang, Shibin Zheng, Yezhou Yang

We study the problem of learning a generalizable action policy for an intelligent agent to actively approach an object of interest in an indoor environment solely from its visual inputs.

Semantic Segmentation Visual Navigation

Learning to Blend Photos

1 code implementation ECCV 2018 Wei-Chih Hung, Jianming Zhang, Xiaohui Shen, Zhe Lin, Joon-Young Lee, Ming-Hsuan Yang

Specifically, given a foreground image and a background image, our proposed method automatically generates a set of blending photos with scores that indicate the aesthetics quality with the proposed quality network and policy network.

Compositing-aware Image Search

no code implementations ECCV 2018 Hengshuang Zhao, Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli, Brian Price, Jiaya Jia

We present a new image search technique that, given a background image, returns compatible foreground objects for image compositing tasks.

Image Retrieval

Concept Mask: Large-Scale Segmentation from Semantic Concepts

no code implementations ECCV 2018 Yufei Wang, Zhe Lin, Xiaohui Shen, Jianming Zhang, Scott Cohen

Then, we refine and extend the embedding network to predict an attention map, using a curated dataset with bounding box annotations on 750 concepts.

Semantic Segmentation

Active Object Perceiver: Recognition-guided Policy Learning for Object Searching on Mobile Robots

no code implementations30 Jul 2018 Xin Ye, Zhe Lin, Haoxiang Li, Shibin Zheng, Yezhou Yang

We study the problem of learning a navigation policy for a robot to actively search for an object of interest in an indoor environment solely from its visual inputs.

Object Recognition Visual Navigation

Learning to Understand Image Blur

no code implementations CVPR 2018 Shanghang Zhang, Xiaohui Shen, Zhe Lin, Radomír Měch, João P. Costeira, José M. F. Moura

In this paper, we propose a unified framework to estimate a spatially-varying blur map and understand its desirability in terms of image quality at the same time.

Reference-Conditioned Super-Resolution by Neural Texture Transfer

no code implementations10 Apr 2018 Zhifei Zhang, Zhaowen Wang, Zhe Lin, Hairong Qi

We focus on transferring the high-resolution texture from reference images to the super-resolution process without the constraint of content similarity between reference and target images, which is a key difference from previous example-based methods.

Image Stylization Image Super-Resolution

The AdobeIndoorNav Dataset: Towards Deep Reinforcement Learning based Real-world Indoor Robot Visual Navigation

1 code implementation24 Feb 2018 Kaichun Mo, Haoxiang Li, Zhe Lin, Joon-Young Lee

Synthetic data suffers from domain gap to the real-world scenes while visual inputs rendered from 3D reconstructed scenes have undesired holes and artifacts.

Robotics

Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers

1 code implementation ICLR 2018 Jianbo Ye, Xin Lu, Zhe Lin, James Z. Wang

Model pruning has become a useful technique that improves the computational efficiency of deep learning, making it possible to deploy solutions in resource-limited scenarios.

Generative Image Inpainting with Contextual Attention

25 code implementations CVPR 2018 Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, Thomas S. Huang

Motivated by these observations, we propose a new deep generative model-based approach which can not only synthesize novel image structures but also explicitly utilize surrounding image features as references during network training to make better predictions.

Image Inpainting

Contextual-based Image Inpainting: Infer, Match, and Translate

no code implementations ECCV 2018 Yuhang Song, Chao Yang, Zhe Lin, Xiaofeng Liu, Qin Huang, Hao Li, C. -C. Jay Kuo

We study the task of image inpainting, which is to fill in the missing region of an incomplete image with plausible contents.

Image Inpainting Translation

Predicting Scene Parsing and Motion Dynamics in the Future

no code implementations NeurIPS 2017 Xiaojie Jin, Huaxin Xiao, Xiaohui Shen, Jimei Yang, Zhe Lin, Yunpeng Chen, Zequn Jie, Jiashi Feng, Shuicheng Yan

The ability of predicting the future is important for intelligent systems, e. g. autonomous vehicles and robots to plan early and make decisions accordingly.

Autonomous Vehicles motion prediction +2

Scene Parsing with Global Context Embedding

1 code implementation ICCV 2017 Wei-Chih Hung, Yi-Hsuan Tsai, Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli, Xin Lu, Ming-Hsuan Yang

We present a scene parsing method that utilizes global context information based on both the parametric and non- parametric models.

Scene Parsing

Personalized Image Aesthetics

no code implementations ICCV 2017 Jian Ren, Xiaohui Shen, Zhe Lin, Radomir Mech, David J. Foran

To accommodate our study, we first collect two distinct datasets, a large image dataset from Flickr and annotated by Amazon Mechanical Turk, and a small dataset of real personal albums rated by owners.

Active Learning

FoveaNet: Perspective-aware Urban Scene Parsing

no code implementations ICCV 2017 Xin Li, Zequn Jie, Wei Wang, Changsong Liu, Jimei Yang, Xiaohui Shen, Zhe Lin, Qiang Chen, Shuicheng Yan, Jiashi Feng

Thus, they suffer from heterogeneous object scales caused by perspective projection of cameras on actual scenes and inevitably encounter parsing failures on distant objects as well as other boundary and recognition errors.

Scene Parsing

Recognizing and Curating Photo Albums via Event-Specific Image Importance

no code implementations19 Jul 2017 Yufei Wang, Zhe Lin, Xiaohui Shen, Radomir Mech, Gavin Miller, Garrison W. Cottrell

Automatic organization of personal photos is a problem with many real world ap- plications, and can be divided into two main tasks: recognizing the event type of the photo collection, and selecting interesting images from the collection.

Spatial-Semantic Image Search by Visual Feature Synthesis

no code implementations CVPR 2017 Long Mai, Hailin Jin, Zhe Lin, Chen Fang, Jonathan Brandt, Feng Liu

We train a convolutional neural network to synthesize appropriate visual features that captures the spatial-semantic constraints from the user canvas query.

Image Retrieval

Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition

no code implementations CVPR 2017 Yufei Wang, Zhe Lin, Xiaohui Shen, Scott Cohen, Garrison W. Cottrell

Furthermore, our algorithm can generate descriptions with varied length, benefiting from the separate control of the skeleton and attributes.

Image Captioning Language Modelling

Recurrent Multimodal Interaction for Referring Image Segmentation

1 code implementation ICCV 2017 Chenxi Liu, Zhe Lin, Xiaohui Shen, Jimei Yang, Xin Lu, Alan Yuille

In this paper we are interested in the problem of image segmentation given natural language descriptions, i. e. referring expressions.

Semantic Segmentation

Learning to Detect Multiple Photographic Defects

1 code implementation6 Dec 2016 Ning Yu, Xiaohui Shen, Zhe Lin, Radomir Mech, Connelly Barnes

Our new dataset enables us to formulate the problem as a multi-task learning problem and train a multi-column deep convolutional neural network (CNN) to simultaneously predict the severity of all the defects.

Defect Detection Multi-Task Learning

Video Scene Parsing with Predictive Feature Learning

no code implementations ICCV 2017 Xiaojie Jin, Xin Li, Huaxin Xiao, Xiaohui Shen, Zhe Lin, Jimei Yang, Yunpeng Chen, Jian Dong, Luoqi Liu, Zequn Jie, Jiashi Feng, Shuicheng Yan

In this way, the network can effectively learn to capture video dynamics and temporal context, which are critical clues for video scene parsing, without requiring extra manual annotations.

Representation Learning Scene Parsing

High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis

1 code implementation CVPR 2017 Chao Yang, Xin Lu, Zhe Lin, Eli Shechtman, Oliver Wang, Hao Li

Recent advances in deep learning have shown exciting promise in filling large holes in natural images with semantically plausible and context aware details, impacting fundamental image manipulation tasks such as object removal.

Image Inpainting Image Manipulation

Proposing Plausible Answers for Open-ended Visual Question Answering

no code implementations20 Oct 2016 Omid Bakhshandeh, Trung Bui, Zhe Lin, Walter Chang

One of the most interesting recent open-ended question answering challenges is Visual Question Answering (VQA) which attempts to evaluate a system's visual understanding through its answers to natural language questions about images.

Graph Matching Question Answering +1

Top-down Neural Attention by Excitation Backprop

2 code implementations1 Aug 2016 Jianming Zhang, Zhe Lin, Jonathan Brandt, Xiaohui Shen, Stan Sclaroff

We aim to model the top-down attention of a Convolutional Neural Network (CNN) classifier for generating task-specific attention maps.

Salient Object Subitizing

no code implementations CVPR 2015 Jianming Zhang, Shugao Ma, Mehrnoosh Sameki, Stan Sclaroff, Margrit Betke, Zhe Lin, Xiaohui Shen, Brian Price, Radomir Mech

We study the problem of Salient Object Subitizing, i. e. predicting the existence and the number of salient objects in an image using holistic cues.

Image Retrieval RGB Salient Object Detection +1

Progressive Attention Networks for Visual Attribute Prediction

1 code implementation8 Jun 2016 Paul Hongsuck Seo, Zhe Lin, Scott Cohen, Xiaohui Shen, Bohyung Han

We propose a novel attention model that can accurately attends to target objects of various scales and shapes in images.

Photo Aesthetics Ranking Network with Attributes and Content Adaptation

2 code implementations6 Jun 2016 Shu Kong, Xiaohui Shen, Zhe Lin, Radomir Mech, Charless Fowlkes

In this work, we propose to learn a deep convolutional neural network to rank photo aesthetics in which the relative ranking of photo aesthetics are directly modeled in the loss function.

Aesthetics Quality Assessment

A Multi-Level Contextual Model For Person Recognition in Photo Albums

no code implementations CVPR 2016 Haoxiang Li, Jonathan Brandt, Zhe Lin, Xiaohui Shen, Gang Hua

Our new framework enables efficient use of these complementary multi-level contextual cues to improve overall recognition rates on the photo album person recognition task, as demonstrated through state-of-the-art results on a challenging public dataset.

Person Recognition

Event-Specific Image Importance

no code implementations CVPR 2016 Yufei Wang, Zhe Lin, Xiaohui Shen, Radomir Mech, Gavin Miller, Garrison W. Cottrell

In this paper, we show that the selection of important images is consistent among different viewers, and that this selection process is related to the event type of the album.

Shortlist Selection With Residual-Aware Distance Estimator for K-Nearest Neighbor Search

no code implementations CVPR 2016 Jae-Pil Heo, Zhe Lin, Xiaohui Shen, Jonathan Brandt, Sung-Eui Yoon

We have tested the proposed method with the inverted index and multi-index on a diverse set of benchmarks including up to one billion data points with varying dimensions, and found that our method robustly improves the accuracy of shortlists (up to 127% relatively higher) over the state-of-the-art techniques with a comparable or even faster computational cost.

Quantization

Multi-Instance Visual-Semantic Embedding

no code implementations22 Dec 2015 Zhou Ren, Hailin Jin, Zhe Lin, Chen Fang, Alan Yuille

Visual-semantic embedding models have been recently proposed and shown to be effective for image classification and zero-shot learning, by mapping images into a continuous semantic label space.

General Classification Image Classification +1

Minimum Barrier Salient Object Detection at 80 FPS

no code implementations ICCV 2015 Jianming Zhang, Stan Sclaroff, Zhe Lin, Xiaohui Shen, Brian Price, Radomir Mech

Powered by this fast MBD transform algorithm, the proposed salient object detection method runs at 80 FPS, and significantly outperforms previous methods with similar speed on four large benchmark datasets, and achieves comparable or better performance than state-of-the-art methods.

Ranked #6 on Video Salient Object Detection on DAVSOD-easy35 (using extra training data)

Salient Object Detection Video Salient Object Detection

Automatic Content-Aware Color and Tone Stylization

no code implementations CVPR 2016 Joon-Young Lee, Kalyan Sunkavalli, Zhe Lin, Xiaohui Shen, In So Kweon

We introduce a new technique that automatically generates diverse, visually compelling stylizations for a photograph in an unsupervised manner.

Style Transfer

LCNN: Low-level Feature Embedded CNN for Salient Object Detection

no code implementations17 Aug 2015 Hongyang Li, Huchuan Lu, Zhe Lin, Xiaohui Shen, Brian Price

In this paper, we propose a novel deep neural network framework embedded with low-level features (LCNN) for salient object detection in complex images.

RGB Salient Object Detection Salient Object Detection

A Convolutional Neural Network Cascade for Face Detection

no code implementations CVPR 2015 Haoxiang Li, Zhe Lin, Xiaohui Shen, Jonathan Brandt, Gang Hua

To improve localization effectiveness, and reduce the number of candidates at later stages, we introduce a CNN-based calibration stage after each of the detection stages in the cascade.

Face Detection

PatchCut: Data-Driven Object Segmentation via Local Shape Transfer

no code implementations CVPR 2015 Jimei Yang, Brian Price, Scott Cohen, Zhe Lin, Ming-Hsuan Yang

The transferred local shape masks constitute a patch-level segmentation solution space and we thus develop a novel cascade algorithm, PatchCut, for coarse-to-fine object segmentation.

Object Discovery Semantic Segmentation

Towards Unified Depth and Semantic Prediction From a Single Image

no code implementations CVPR 2015 Peng Wang, Xiaohui Shen, Zhe Lin, Scott Cohen, Brian Price, Alan L. Yuille

By allowing for interactions between the depth and semantic information, the joint network provides more accurate depth prediction than a state-of-the-art CNN trained solely for depth prediction [5].

Depth Estimation Semantic Segmentation

Inner and Inter Label Propagation: Salient Object Detection in the Wild

2 code implementations27 May 2015 Hongyang Li, Huchuan Lu, Zhe Lin, Xiaohui Shen, Brian Price

For most natural images, some boundary superpixels serve as the background labels and the saliency of other superpixels are determined by ranking their similarities to the boundary labels based on an inner propagation scheme.

RGB Salient Object Detection Saliency Detection +1

Joint Object and Part Segmentation using Deep Learned Potentials

no code implementations ICCV 2015 Peng Wang, Xiaohui Shen, Zhe Lin, Scott Cohen, Brian Price, Alan Yuille

Segmenting semantic objects from images and parsing them into their respective semantic parts are fundamental steps towards detailed object understanding in computer vision.

Semantic Segmentation

Collaborative Feature Learning from Social Media

no code implementations CVPR 2015 Chen Fang, Hailin Jin, Jianchao Yang, Zhe Lin

We validate our feature learning paradigm on this dataset and find that the learned feature significantly outperforms the state-of-the-art image features in learning better image similarities.

Efficient Boosted Exemplar-based Face Detection

no code implementations CVPR 2014 Haoxiang Li, Zhe Lin, Jonathan Brandt, Xiaohui Shen, Gang Hua

Despite the fact that face detection has been studied intensively over the past several decades, the problem is still not completely solved.

Face Detection

Nonparametric Context Modeling of Local Appearance for Pose- and Expression-Robust Facial Landmark Localization

no code implementations CVPR 2014 Brandon M. Smith, Jonathan Brandt, Zhe Lin, Li Zhang

We propose a data-driven approach to facial landmark localization that models the correlations between each landmark and its surrounding appearance features.

Face Alignment

Distance Encoded Product Quantization

no code implementations CVPR 2014 Jae-Pil Heo, Zhe Lin, Sung-Eui Yoon

This result is achieved mainly because our method accurately estimates distances between two data points with the new binary codes and distance metric.

Quantization

Scalable Similarity Learning using Large Margin Neighborhood Embedding

no code implementations24 Apr 2014 Zhaowen Wang, Jianchao Yang, Zhe Lin, Jonathan Brandt, Shiyu Chang, Thomas Huang

In this paper, we present an image similarity learning method that can scale well in both the number of images and the dimensionality of image descriptors.

Metric Learning

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

no code implementations21 Dec 2013 Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin, Thomas Huang

The ability to train large-scale neural networks has resulted in state-of-the-art performance in many areas of computer vision.

Probabilistic Elastic Matching for Pose Variant Face Verification

no code implementations CVPR 2013 Haoxiang Li, Gang Hua, Zhe Lin, Jonathan Brandt, Jianchao Yang

By augmenting each feature with its location, a Gaussian mixture model (GMM) is trained to capture the spatialappearance distribution of all face images in the training corpus.

Face Recognition Face Verification

Large Displacement Optical Flow from Nearest Neighbor Fields

no code implementations CVPR 2013 Zhuoyuan Chen, Hailin Jin, Zhe Lin, Scott Cohen, Ying Wu

We use approximate nearest neighbor fields to compute an initial motion field and use a robust algorithm to compute a set of similarity transformations as the motion candidates for segmentation.

Motion Estimation Motion Segmentation +1

Detecting and Aligning Faces by Image Retrieval

no code implementations CVPR 2013 Xiaohui Shen, Zhe Lin, Jonathan Brandt, Ying Wu

In order to overcome these challenges, we present a novel and robust exemplarbased face detector that integrates image retrieval and discriminative learning.

Face Alignment Face Detection +2

Fast Image Super-Resolution Based on In-Place Example Regression

no code implementations CVPR 2013 Jianchao Yang, Zhe Lin, Scott Cohen

Extensive experiments on benchmark and realworld images demonstrate that our algorithm can produce natural-looking results with sharp edges and preserved fine details, while the current state-of-the-art algorithms are prone to visual artifacts.

Image Super-Resolution

Exemplar-Based Face Parsing

no code implementations CVPR 2013 Brandon M. Smith, Li Zhang, Jonathan Brandt, Zhe Lin, Jianchao Yang

Given a test image, our algorithm first selects a subset of exemplar images from the database, Our algorithm then computes a nonrigid warp for each exemplar image to align it with the test image.

Face Alignment Face Parsing +1

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