Search Results for author: Jiwen Lu

Found 111 papers, 41 papers with code

Temporal Coherence or Temporal Motion: Which is More Critical for Video-based Person Re-identification?

no code implementations ECCV 2020 Guangyi Chen, Yongming Rao, Jiwen Lu, Jie zhou

Specifically, we disentangle the video representation into the temporal coherence and motion parts and randomly change the scale of the temporal motion features as the adversarial noise.

Video-Based Person Re-Identification

Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification

no code implementations ECCV 2020 Guangyi Chen, Yuhao Lu, Jiwen Lu, Jie Zhou

Experimental results demonstrate that our DCML method explores credible and valuable training data and improves the performance of unsupervised domain adaptation.

Metric Learning Person Re-Identification +1

Rotation-robust Intersection over Union for 3D Object Detection

no code implementations ECCV 2020 Yu Zheng, Danyang Zhang, Sinan Xie, Jiwen Lu, Jie zhou

In this paper, we propose a Rotation-robust Intersection over Union ($ extit{RIoU}$) for 3D object detection, which aims to jointly learn the overlap of rotated bounding boxes.

3D Object Detection

Deep Hashing with Active Pairwise Supervision

no code implementations ECCV 2020 Ziwei Wang, Quan Zheng, Jiwen Lu, Jie zhou

n this paper, we propose a Deep Hashing method with Active Pairwise Supervision(DH-APS).

Structural Deep Metric Learning for Room Layout Estimation

no code implementations ECCV 2020 Wenzhao Zheng, Jiwen Lu, Jie zhou

We employ a metric model and a layout encoder to map the RGB images and the ground-truth layouts to the embedding space, respectively, and a layout decoder to map the embeddings to the corresponding layouts, where the whole framework is trained in an end-to-end manner.

Metric Learning Room Layout Estimation

Spatial Geometric Reasoning for Room Layout Estimation via Deep Reinforcement Learning

no code implementations ECCV 2020 Liangliang Ren, Yangyang Song, Jiwen Lu, Jie zhou

Unlike most existing works that define room layout on a 2D image, we model the layout in 3D as a configuration of the camera and the room.

Robot Navigation Room Layout Estimation

Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network

1 code implementation17 Dec 2021 An Tao, Yueqi Duan, He Wang, Ziyi Wu, Pengliang Ji, Haowen Sun, Jie zhou, Jiwen Lu

It results in a serious issue of lagged gradient, making the learned attack at the current step ineffective due to the architecture changes afterward.

Adversarial Attack Semantic Segmentation

DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting

1 code implementation2 Dec 2021 Yongming Rao, Wenliang Zhao, Guangyi Chen, Yansong Tang, Zheng Zhu, Guan Huang, Jie zhou, Jiwen Lu

In this work, we present a new framework for dense prediction by implicitly and explicitly leveraging the pre-trained knowledge from CLIP.

Instance Segmentation Language Modelling +4

Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation

1 code implementation17 Oct 2021 Yinghuan Shi, Jian Zhang, Tong Ling, Jiwen Lu, Yefeng Zheng, Qian Yu, Lei Qi, Yang Gao

In semi-supervised medical image segmentation, most previous works draw on the common assumption that higher entropy means higher uncertainty.

Medical Image Segmentation

Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search

no code implementations29 Sep 2021 Han Xiao, Ziwei Wang, Jiwen Lu, Jie zhou

In this paper, we propose a Shapley value based operation contribution evaluation method (Shapley-NAS) for neural architecture search.

Image Classification Neural Architecture Search

Structure-Preserving Image Super-Resolution

1 code implementation26 Sep 2021 Cheng Ma, Yongming Rao, Jiwen Lu, Jie zhou

Firstly, we propose SPSR with gradient guidance (SPSR-G) by exploiting gradient maps of images to guide the recovery in two aspects.

Image Super-Resolution SSIM

NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo

1 code implementation ICCV 2021 Yi Wei, Shaohui Liu, Yongming Rao, Wang Zhao, Jiwen Lu, Jie zhou

In this work, we present a new multi-view depth estimation method that utilizes both conventional reconstruction and learning-based priors over the recently proposed neural radiance fields (NeRF).

Depth Estimation

Diverse Sample Generation: Pushing the Limit of Data-free Quantization

1 code implementation1 Sep 2021 Haotong Qin, Yifu Ding, Xiangguo Zhang, Aoyu Li, Jiakai Wang, Xianglong Liu, Jiwen Lu

Recently, generative data-free quantization emerges as a practical approach that compresses the neural network to low bit-width without access to real data.

Image Classification Quantization

Deep Relational Metric Learning

1 code implementation ICCV 2021 Wenzhao Zheng, Borui Zhang, Jiwen Lu, Jie zhou

This paper presents a deep relational metric learning (DRML) framework for image clustering and retrieval.

Image Clustering Metric Learning

PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

1 code implementation ICCV 2021 Xumin Yu, Yongming Rao, Ziyi Wang, Zuyan Liu, Jiwen Lu, Jie zhou

In this paper, we present a new method that reformulates point cloud completion as a set-to-set translation problem and design a new model, called PoinTr that adopts a transformer encoder-decoder architecture for point cloud completion.

Point Cloud Completion

Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

1 code implementation ICCV 2021 Yongming Rao, Guangyi Chen, Jiwen Lu, Jie zhou

Unlike most existing methods that learn visual attention based on conventional likelihood, we propose to learn the attention with counterfactual causality, which provides a tool to measure the attention quality and a powerful supervisory signal to guide the learning process.

Causal Inference Fine-Grained Image Classification +5

RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection

no code implementations ICCV 2021 Yongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie zhou

In particular, we propose to generate random layouts of a scene by making use of the objects in the synthetic CAD dataset and learn the 3D scene representation by applying object-level contrastive learning on two random scenes generated from the same set of synthetic objects.

3D Object Detection Contrastive Learning +1

Person Re-identification via Attention Pyramid

1 code implementation11 Aug 2021 Guangyi Chen, Tianpei Gu, Jiwen Lu, Jin-An Bao, Jie zhou

Experimental results demonstrate the superiority of our method, which outperforms the state-of-the-art methods by a large margin with limited computational cost.

Person Re-Identification

Generalizable Mixed-Precision Quantization via Attribution Rank Preservation

1 code implementation ICCV 2021 Ziwei Wang, Han Xiao, Jiwen Lu, Jie zhou

On the contrary, our GMPQ searches the mixed-quantization policy that can be generalized to largescale datasets with only a small amount of data, so that the search cost is significantly reduced without performance degradation.

Quantization

Human Trajectory Prediction via Counterfactual Analysis

1 code implementation ICCV 2021 Guangyi Chen, Junlong Li, Jiwen Lu, Jie zhou

Most existing methods learn to predict future trajectories by behavior clues from history trajectories and interaction clues from environments.

Autonomous Vehicles Trajectory Forecasting

Personalized Trajectory Prediction via Distribution Discrimination

1 code implementation ICCV 2021 Guangyi Chen, Junlong Li, Nuoxing Zhou, Liangliang Ren, Jiwen Lu

In this paper, we present a distribution discrimination (DisDis) method to predict personalized motion patterns by distinguishing the potential distributions.

Trajectory Prediction

Similarity-Aware Fusion Network for 3D Semantic Segmentation

1 code implementation4 Jul 2021 Linqing Zhao, Jiwen Lu, Jie zhou

To address this, we employ a late fusion strategy where we first learn the geometric and contextual similarities between the input and back-projected (from 2D pixels) point clouds and utilize them to guide the fusion of two modalities to further exploit complementary information.

3D Semantic Segmentation

Global Filter Networks for Image Classification

3 code implementations NeurIPS 2021 Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie zhou

Recent advances in self-attention and pure multi-layer perceptrons (MLP) models for vision have shown great potential in achieving promising performance with fewer inductive biases.

Ranked #8 on Image Classification on Stanford Cars (using extra training data)

Domain Generalization Image Classification

Self-Supervised Video Hashing via Bidirectional Transformers

1 code implementation CVPR 2021 Shuyan Li, Xiu Li, Jiwen Lu, Jie zhou

Most existing unsupervised video hashing methods are built on unidirectional models with less reliable training objectives, which underuse the correlations among frames and the similarity structure between videos.

Video Retrieval

Deep Compositional Metric Learning

1 code implementation CVPR 2021 Wenzhao Zheng, Chengkun Wang, Jiwen Lu, Jie zhou

In this paper, we propose a deep compositional metric learning (DCML) framework for effective and generalizable similarity measurement between images.

Metric Learning

Structure-Aware Face Clustering on a Large-Scale Graph With 107 Nodes

1 code implementation CVPR 2021 Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou

To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.

Face Clustering Graph Clustering

Pseudo Facial Generation With Extreme Poses for Face Recognition

no code implementations CVPR 2021 Guoli Wang, Jiaqi Ma, Qian Zhang, Jiwen Lu, Jie zhou

Many of them settle it by generating fake frontal faces from extreme ones, whereas they are tough to maintain the identity information with high computational consumption and uncontrolled disturbances.

Face Recognition

DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

1 code implementation NeurIPS 2021 Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie zhou, Cho-Jui Hsieh

Based on this observation, we propose a dynamic token sparsification framework to prune redundant tokens progressively and dynamically based on the input.

Image Classification

FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection

1 code implementation17 May 2021 Yi Wei, Shang Su, Jiwen Lu, Jie zhou

To tackle this problem, we propose frustum-aware geometric reasoning (FGR) to detect vehicles in point clouds without any 3D annotations.

3D Object Detection

SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation

no code implementations6 Apr 2021 Jiabin Zhang, Zheng Zhu, Jiwen Lu, JunJie Huang, Guan Huang, Jie zhou

To make a better trade-off between accuracy and efficiency, we propose a novel multi-person pose estimation framework, SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation (SIMPLE).

Human Detection Multi-Person Pose Estimation

Meta-Mining Discriminative Samples for Kinship Verification

no code implementations CVPR 2021 Wanhua Li, Shiwei Wang, Jiwen Lu, Jianjiang Feng, Jie zhou

In the end, the samples in the unbalanced train batch are re-weighted by the learned meta-miner to optimize the kinship models.

Structure-Aware Face Clustering on a Large-Scale Graph with $\bf{10^{7}}$ Nodes

no code implementations24 Mar 2021 Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou

To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.

Face Clustering Graph Clustering

WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition

no code implementations CVPR 2021 Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jiwen Lu, Dalong Du, Jie zhou

In this paper, we contribute a new million-scale face benchmark containing noisy 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training data, as well as an elaborately designed time-constrained evaluation protocol.

 Ranked #1 on Face Verification on IJB-C (using extra training data)

Face Recognition Face Verification

Separable Structure Modeling for Semi-supervised Video Object Segmentation

1 code implementation18 Feb 2021 Wencheng Zhu, Jiahao Li, Jiwen Lu, Jie zhou

Specifically, we first compute a pixel-wise similarity matrix by using representations of reference and target pixels and then select top-rank reference pixels for target pixel classification.

One-shot visual object segmentation Video Semantic Segmentation

Rank-Consistency Deep Hashing for Scalable Multi-Label Image Search

no code implementations2 Feb 2021 Cheng Ma, Jiwen Lu, Jie zhou

As hashing becomes an increasingly appealing technique for large-scale image retrieval, multi-label hashing is also attracting more attention for the ability to exploit multi-level semantic contents.

Image Retrieval Semantic Similarity +1

SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images

no code implementations19 Jan 2021 Lei He, Jiwen Lu, Guanghui Wang, Shiyu Song, Jie zhou

In this paper, we first introduce the concept of semantic objectness to exploit the geometric relationship of these two tasks through an analysis of the imaging process, then propose a Semantic Object Segmentation and Depth Estimation Network (SOSD-Net) based on the objectness assumption.

Monocular Depth Estimation Multi-Task Learning +2

Frequency-Aware Spatiotemporal Transformers for Video Inpainting Detection

no code implementations ICCV 2021 Bingyao Yu, Wanhua Li, Xiu Li, Jiwen Lu, Jie zhou

In this paper, we propose a frequency-aware spatiotemporal transformers for deep In this paper, we propose a Frequency-Aware Spatiotemporal Transformer (FAST) for video inpainting detection, which aims to simultaneously mine the traces of video inpainting from spatial, temporal, and frequency domains.

Video Inpainting

SegGroup: Seg-Level Supervision for 3D Instance and Semantic Segmentation

2 code implementations18 Dec 2020 An Tao, Yueqi Duan, Yi Wei, Jiwen Lu, Jie zhou

Most existing point cloud instance and semantic segmentation methods rely heavily on strong supervision signals, which require point-level labels for every point in the scene.

Point Cloud Segmentation Scene Segmentation

PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds

1 code implementation CVPR 2021 Yi Wei, Ziyi Wang, Yongming Rao, Jiwen Lu, Jie zhou

In this paper, we propose a Point-Voxel Recurrent All-Pairs Field Transforms (PV-RAFT) method to estimate scene flow from point clouds.

Scene Flow Estimation

DSNet: A Flexible Detect-to-Summarize Network for Video Summarization

1 code implementation1 Dec 2020 Wencheng Zhu, Jiwen Lu, Jiahao Li, and Jie Zhou

In this paper, we propose a Detect-to-Summarize network (DSNet) framework for supervised video summarization.

Supervised Video Summarization

Graph-Based Social Relation Reasoning

1 code implementation ECCV 2020 Wanhua Li, Yueqi Duan, Jiwen Lu, Jianjiang Feng, Jie zhou

Human beings are fundamentally sociable -- that we generally organize our social lives in terms of relations with other people.

Relational Reasoning

Latent Fingerprint Registration via Matching Densely Sampled Points

no code implementations12 May 2020 Shan Gu, Jianjiang Feng, Jiwen Lu, Jie zhou

Given a pair of fingerprints to match, we bypass the minutiae extraction step and take uniformly sampled points as key points.

Graph-based Kinship Reasoning Network

no code implementations22 Apr 2020 Wanhua Li, Yingqiang Zhang, Kangchen Lv, Jiwen Lu, Jianjiang Feng, Jie zhou

In this paper, we propose a graph-based kinship reasoning (GKR) network for kinship verification, which aims to effectively perform relational reasoning on the extracted features of an image pair.

Relational Reasoning

Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark Estimation

1 code implementation CVPR 2020 Cheng Ma, Zhenyu Jiang, Yongming Rao, Jiwen Lu, Jie zhou

In this paper, we propose a deep face super-resolution (FSR) method with iterative collaboration between two recurrent networks which focus on facial image recovery and landmark estimation respectively.

Super-Resolution

Structure-Preserving Super Resolution with Gradient Guidance

2 code implementations CVPR 2020 Cheng Ma, Yongming Rao, Yean Cheng, Ce Chen, Jiwen Lu, Jie zhou

In this paper, we propose a structure-preserving super resolution method to alleviate the above issue while maintaining the merits of GAN-based methods to generate perceptual-pleasant details.

Image Super-Resolution SSIM

Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds

1 code implementation CVPR 2020 Yongming Rao, Jiwen Lu, Jie zhou

Based on this hypothesis, we propose to learn point cloud representation by bidirectional reasoning between the local structures at different abstraction hierarchies and the global shape without human supervision.

3D Object Classification General Classification +1

Comprehensive Instructional Video Analysis: The COIN Dataset and Performance Evaluation

no code implementations20 Mar 2020 Yansong Tang, Jiwen Lu, Jie zhou

We believe the introduction of the COIN dataset will promote the future in-depth research on instructional video analysis for the community.

Action Detection

BiDet: An Efficient Binarized Object Detector

1 code implementation CVPR 2020 Ziwei Wang, Ziyi Wu, Jiwen Lu, Jie zhou

Conventional network binarization methods directly quantize the weights and activations in one-stage or two-stage detectors with constrained representational capacity, so that the information redundancy in the networks causes numerous false positives and degrades the performance significantly.

Binarization Object Detection

DotFAN: A Domain-transferred Face Augmentation Network for Pose and Illumination Invariant Face Recognition

no code implementations23 Feb 2020 Hao-Chiang Shao, Kang-Yu Liu, Chia-Wen Lin, Jiwen Lu

With their aid, DotFAN can learn a disentangled face representation and effectively generate face images of various facial attributes while preserving the identity of augmented faces.

Face Recognition

P$^2$GNet: Pose-Guided Point Cloud Generating Networks for 6-DoF Object Pose Estimation

no code implementations19 Dec 2019 Peiyu Yu, Yongming Rao, Jiwen Lu, Jie zhou

Humans are able to perform fast and accurate object pose estimation even under severe occlusion by exploiting learned object model priors from everyday life.

6D Pose Estimation 6D Pose Estimation using RGB

Automatic Data Augmentation by Learning the Deterministic Policy

1 code implementation18 Oct 2019 Yinghuan Shi, Tiexin Qin, Yong liu, Jiwen Lu, Yang Gao, Dinggang Shen

By introducing an unified optimization goal, DeepAugNet intends to combine the data augmentation and the deep model training in an end-to-end training manner which is realized by simultaneously training a hybrid architecture of dueling deep Q-learning algorithm and a surrogate deep model.

Data Augmentation Q-Learning

Improving Sample-based Evaluation for Generative Adversarial Networks

no code implementations ICLR 2019 Shaohui Liu*, Yi Wei*, Jiwen Lu, Jie zhou

Unlike most existing evaluation frameworks which transfer the representation of ImageNet inception model to map images onto the feature space, our framework uses a specialized encoder to acquire fine-grained domain-specific representation.

Deep Fitting Degree Scoring Network for Monocular 3D Object Detection

no code implementations CVPR 2019 Lijie Liu, Jiwen Lu, Chunjing Xu, Qi Tian, Jie zhou

In this paper, we propose to learn a deep fitting degree scoring network for monocular 3D object detection, which aims to score fitting degree between proposals and object conclusively.

Monocular 3D Object Detection Vehicle Pose Estimation

BridgeNet: A Continuity-Aware Probabilistic Network for Age Estimation

no code implementations CVPR 2019 Wanhua Li, Jiwen Lu, Jianjiang Feng, Chunjing Xu, Jie zhou, Qi Tian

Existing methods for age estimation usually apply a divide-and-conquer strategy to deal with heterogeneous data caused by the non-stationary aging process.

Age Estimation

Hardness-Aware Deep Metric Learning

2 code implementations CVPR 2019 Wenzhao Zheng, Zhaodong Chen, Jiwen Lu, Jie zhou

This paper presents a hardness-aware deep metric learning (HDML) framework.

Ranked #15 on Metric Learning on CUB-200-2011 (using extra training data)

Image Retrieval Metric Learning

COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

no code implementations CVPR 2019 Yansong Tang, Dajun Ding, Yongming Rao, Yu Zheng, Danyang Zhang, Lili Zhao, Jiwen Lu, Jie zhou

There are substantial instructional videos on the Internet, which enables us to acquire knowledge for completing various tasks.

Action Detection

Part-Activated Deep Reinforcement Learning for Action Prediction

no code implementations ECCV 2018 Lei Chen, Jiwen Lu, Zhanjie Song, Jie zhou

In this paper, we propose a part-activated deep reinforcement learning (PA-DRL) for action prediction.

Deep Reinforcement Learning with Iterative Shift for Visual Tracking

no code implementations ECCV 2018 Liangliang Ren, Xin Yuan, Jiwen Lu, Ming Yang, Jie Zhou

Visual tracking is confronted by the dilemma to locate a target both}accurately and efficiently, and make decisions online whether and how to adapt the appearance model or even restart tracking.

Motion Estimation Object Tracking +1

Dual-Agent Deep Reinforcement Learning for Deformable Face Tracking

no code implementations ECCV 2018 Minghao Guo, Jiwen Lu, Jie zhou

In this paper, we propose a dual-agent deep reinforcement learning (DADRL) method for deformable face tracking, which generates bounding boxes and detects facial landmarks interactively from face videos.

Facial Landmark Detection

Collaborative Deep Reinforcement Learning for Multi-Object Tracking

no code implementations ECCV 2018 Liangliang Ren, Jiwen Lu, Zifeng Wang, Qi Tian, Jie zhou

To address this, we develop a deep prediction-decision network in our C-DRL, which simultaneously detects and predicts objects under a unified network via deep reinforcement learning.

Multi-Object Tracking

Deep Variational Metric Learning

no code implementations ECCV 2018 Xudong Lin, Yueqi Duan, Qiyuan Dong, Jiwen Lu, Jie zhou

Deep metric learning has been extensively explored recently, which trains a deep neural network to produce discriminative embedding features.

Metric Learning

Graininess-Aware Deep Feature Learning for Pedestrian Detection

no code implementations ECCV 2018 Chunze Lin, Jiwen Lu, Gang Wang, Jie zhou

In this paper, we propose a graininess-aware deep feature learning method for pedestrian detection.

Pedestrian Detection

Relaxation-Free Deep Hashing via Policy Gradient

no code implementations ECCV 2018 Xin Yuan, Liangliang Ren, Jiwen Lu, Jie zhou

In this paper, we propose a simple yet effective relaxation-free method to learn more effective binary codes via policy gradient for scalable image search.

Image Retrieval

Deep Hashing via Discrepancy Minimization

no code implementations CVPR 2018 Zhixiang Chen, Xin Yuan, Jiwen Lu, Qi Tian, Jie zhou

This paper presents a discrepancy minimizing model to address the discrete optimization problem in hashing learning.

Deep Adversarial Metric Learning

no code implementations CVPR 2018 Yueqi Duan, Wenzhao Zheng, Xudong Lin, Jiwen Lu, Jie zhou

Learning an effective distance metric between image pairs plays an important role in visual analysis, where the training procedure largely relies on hard negative samples.

Metric Learning

Learning Globally Optimized Object Detector via Policy Gradient

no code implementations CVPR 2018 Yongming Rao, Dahua Lin, Jiwen Lu, Jie zhou

In this paper, we propose a simple yet effective method to learn globally optimized detector for object detection, which is a simple modification to the standard cross-entropy gradient inspired by the REINFORCE algorithm.

Object Detection

Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition

no code implementations CVPR 2018 Yansong Tang, Yi Tian, Jiwen Lu, Peiyang Li, Jie zhou

In this paper, we propose a deep progressive reinforcement learning (DPRL) method for action recognition in skeleton-based videos, which aims to distil the most informative frames and discard ambiguous frames in sequences for recognizing actions.

Action Recognition Skeleton Based Action Recognition

GraphBit: Bitwise Interaction Mining via Deep Reinforcement Learning

no code implementations CVPR 2018 Yueqi Duan, Ziwei Wang, Jiwen Lu, Xudong Lin, Jie zhou

Specifically, we design a deep reinforcement learning model to learn the structure of the graph for bitwise interaction mining, reducing the uncertainty of binary codes by maximizing the mutual information with inputs and related bits, so that the ambiguous bits receive additional instruction from the graph for confident binarization.

Binarization Representation Learning

An Improved Evaluation Framework for Generative Adversarial Networks

1 code implementation20 Mar 2018 Shaohui Liu, Yi Wei, Jiwen Lu, Jie zhou

Unlike most existing evaluation frameworks which transfer the representation of ImageNet inception model to map images onto the feature space, our framework uses a specialized encoder to acquire fine-grained domain-specific representation.

Runtime Neural Pruning

no code implementations NeurIPS 2017 Ji Lin, Yongming Rao, Jiwen Lu, Jie zhou

In this paper, we propose a Runtime Neural Pruning (RNP) framework which prunes the deep neural network dynamically at the runtime.

Cross-Modal Deep Variational Hashing

no code implementations ICCV 2017 Venice Erin Liong, Jiwen Lu, Yap-Peng Tan, Jie zhou

In this paper, we propose a cross-modal deep variational hashing (CMDVH) method to learn compact binary codes for cross-modality multimedia retrieval.

Attention-Aware Deep Reinforcement Learning for Video Face Recognition

no code implementations ICCV 2017 Yongming Rao, Jiwen Lu, Jie zhou

In this paper, we propose an attention-aware deep reinforcement learning (ADRL) method for video face recognition, which aims to discard the misleading and confounding frames and find the focuses of attention in face videos for person recognition.

Face Recognition Person Recognition

Learning Discriminative Aggregation Network for Video-Based Face Recognition

no code implementations ICCV 2017 Yongming Rao, Ji Lin, Jiwen Lu, Jie zhou

In this paper, we propose a discriminative aggregation network (DAN) for video face recognition, which aims to integrate information from video frames effectively and efficiently.

Face Recognition Metric Learning

Deep Sparse Subspace Clustering

no code implementations25 Sep 2017 Xi Peng, Jiashi Feng, Shijie Xiao, Jiwen Lu, Zhang Yi, Shuicheng Yan

In this paper, we present a deep extension of Sparse Subspace Clustering, termed Deep Sparse Subspace Clustering (DSSC).

Consistent-Aware Deep Learning for Person Re-Identification in a Camera Network

no code implementations CVPR 2017 Ji Lin, Liangliang Ren, Jiwen Lu, Jianjiang Feng, Jie zhou

In this paper, we propose a consistent-aware deep learning (CADL) framework for person re-identification in a camera network.

Person Re-Identification

Learning Deep Binary Descriptor With Multi-Quantization

no code implementations CVPR 2017 Yueqi Duan, Jiwen Lu, Ziwei Wang, Jianjiang Feng, Jie zhou

In this paper, we propose an unsupervised feature learning method called deep binary descriptor with multi-quantization (DBD-MQ) for visual matching.

Binarization Image Retrieval +1

A Siamese Long Short-Term Memory Architecture for Human Re-Identification

no code implementations European Conference on Computer Vision 2016 Rahul Rama Varior, Bing Shuai, Jiwen Lu, Dong Xu, Gang Wang

Matching pedestrians across multiple camera views known as human re-identification (re-identification) is a challenging problem in visual surveillance.

Person Re-Identification

Learning Compact Binary Descriptors With Unsupervised Deep Neural Networks

no code implementations CVPR 2016 Kevin Lin, Jiwen Lu, Chu-Song Chen, Jie zhou

In this paper, we propose a new unsupervised deep learning approach called DeepBit to learn compact binary descriptor for efficient visual object matching.

Image Retrieval Object Recognition +1

Modality and Component Aware Feature Fusion For RGB-D Scene Classification

no code implementations CVPR 2016 Anran Wang, Jianfei Cai, Jiwen Lu, Tat-Jen Cham

While convolutional neural networks (CNN) have been excellent for object recognition, the greater spatial variability in scene images typically meant that the standard full-image CNN features are suboptimal for scene classification.

General Classification Object Recognition +1

Correlated and Individual Multi-Modal Deep Learning for RGB-D Object Recognition

no code implementations6 Apr 2016 Ziyan Wang, Jiwen Lu, Ruogu Lin, Jianjiang Feng, Jie zhou

Specifically, we construct a pair of deep convolutional neural networks (CNNs) for the RGB and depth data, and concatenate them at the top layer of the network with a loss function which learns a new feature space where both correlated part and the individual part of the RGB-D information are well modelled.

Object Recognition

Multi-task CNN Model for Attribute Prediction

no code implementations4 Jan 2016 Abrar H. Abdulnabi, Gang Wang, Jiwen Lu, Kui Jia

Each CNN will generate attribute-specific feature representations, and then we apply multi-task learning on the features to predict their attributes.

Multi-Task Learning

Local Subspace Collaborative Tracking

no code implementations ICCV 2015 Lin Ma, Xiaoqin Zhang, Weiming Hu, Junliang Xing, Jiwen Lu, Jie zhou

To address this, this paper presents a local subspace collaborative tracking method for robust visual tracking, where multiple linear and nonlinear subspaces are learned to better model the nonlinear relationship of object appearances.

Object Tracking Visual Tracking

MMSS: Multi-Modal Sharable and Specific Feature Learning for RGB-D Object Recognition

no code implementations ICCV 2015 Anran Wang, Jianfei Cai, Jiwen Lu, Tat-Jen Cham

We first construct deep CNN layers for color and depth separately, and then connect them with our carefully designed multi-modal layers, which fuse color and depth information by enforcing a common part to be shared by features of different modalities.

Object Recognition

Multiple Feature Fusion via Weighted Entropy for Visual Tracking

no code implementations ICCV 2015 Lin Ma, Jiwen Lu, Jianjiang Feng, Jie zhou

It is desirable to combine multiple feature descriptors to improve the visual tracking performance because different features can provide complementary information to describe objects of interest.

Visual Object Tracking Visual Tracking

Simultaneous Local Binary Feature Learning and Encoding for Face Recognition

no code implementations ICCV 2015 Jiwen Lu, Venice Erin Liong, Jie zhou

In this paper, we propose a simultaneous local binary feature learning and encoding (SLBFLE) method for face recognition.

Face Recognition

Nonlinear Local Metric Learning for Person Re-identification

no code implementations16 Nov 2015 Siyuan Huang, Jiwen Lu, Jie zhou, Anil K. Jain

In this paper, we propose a nonlinear local metric learning (NLML) method to improve the state-of-the-art performance of person re-identification on public datasets.

Metric Learning Person Re-Identification

Deep Transfer Metric Learning

no code implementations CVPR 2015 Junlin Hu, Jiwen Lu, Yap-Peng Tan

Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same.

Face Verification Metric Learning +1

Deep Hashing for Compact Binary Codes Learning

no code implementations CVPR 2015 Venice Erin Liong, Jiwen Lu, Gang Wang, Pierre Moulin, Jie zhou

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for large scale visual search.

Multi-Manifold Deep Metric Learning for Image Set Classification

no code implementations CVPR 2015 Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, Jie zhou

In this paper, we propose a multi-manifold deep metric learning (MMDML) method for image set classification, which aims to recognize an object of interest from a set of image instances captured from varying viewpoints or under varying illuminations.

General Classification Metric Learning

Automatic Subspace Learning via Principal Coefficients Embedding

no code implementations17 Nov 2014 Xi Peng, Jiwen Lu, Zhang Yi, Rui Yan

In this paper, we address two challenging problems in unsupervised subspace learning: 1) how to automatically identify the feature dimension of the learned subspace (i. e., automatic subspace learning), and 2) how to learn the underlying subspace in the presence of Gaussian noise (i. e., robust subspace learning).

Learning Invariant Color Features for Person Re-Identification

no code implementations4 Oct 2014 Rahul Rama Varior, Gang Wang, Jiwen Lu

We model color feature generation as a learning problem by jointly learning a linear transformation and a dictionary to encode pixel values.

Person Re-Identification

Discriminative Deep Metric Learning for Face Verification in the Wild

no code implementations CVPR 2014 Junlin Hu, Jiwen Lu, Yap-Peng Tan

This paper presents a new discriminative deep metric learning (DDML) method for face verification in the wild.

Face Verification Metric Learning

PCANet: A Simple Deep Learning Baseline for Image Classification?

2 code implementations14 Apr 2014 Tsung-Han Chan, Kui Jia, Shenghua Gao, Jiwen Lu, Zinan Zeng, Yi Ma

In this work, we propose a very simple deep learning network for image classification which comprises only the very basic data processing components: cascaded principal component analysis (PCA), binary hashing, and block-wise histograms.

Face Recognition Face Verification +4

Face Recognition via Globality-Locality Preserving Projections

no code implementations6 Nov 2013 Sheng Huang, Dan Yang, Fei Yang, Yongxin Ge, Xiaohong Zhang, Jiwen Lu

We present an improved Locality Preserving Projections (LPP) method, named Gloablity-Locality Preserving Projections (GLPP), to preserve both the global and local geometric structures of data.

Face Recognition

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