Search Results for author: Bingbing Ni

Found 77 papers, 28 papers with code

Energy Attack: On Transferring Adversarial Examples

no code implementations9 Sep 2021 Ruoxi Shi, Borui Yang, Yangzhou Jiang, Chenglong Zhao, Bingbing Ni

Base on the eigenvalues, we can model the energy distribution of adversarial perturbations.

Adversarial Attack

Cross-category Video Highlight Detection via Set-based Learning

1 code implementation26 Aug 2021 Minghao Xu, Hang Wang, Bingbing Ni, Riheng Zhu, Zhenbang Sun, Changhu Wang

For tackling such practical problem, we propose a Dual-Learner-based Video Highlight Detection (DL-VHD) framework.

Knowledge Distillation Unsupervised Domain Adaptation

Object Wake-up: 3-D Object Reconstruction, Animation, and in-situ Rendering from a Single Image

no code implementations5 Aug 2021 Xinxin Zuo, Ji Yang, Sen Wang, Zhenbo Yu, Xinyu Li, Bingbing Ni, Minglun Gong, Li Cheng

The pipeline of our approach starts by reconstructing and refining a 3-D mesh representation of the object of interest from an input image; its control joints are predicted by exploiting the semantic part segmentation information; the obtained object 3-D mesh is then rigged \& animated by non-rigid deformation, and rendered to perform in-situ motions in its original image space.

Object Reconstruction

Exploring Visual Context for Weakly Supervised Person Search

1 code implementation19 Jun 2021 Yichao Yan, Jinpeng Li, Shengcai Liao, Jie Qin, Bingbing Ni, Xiaokang Yang, Ling Shao

We proposed the first framework to address this novel task, namely Context-Guided Person Search (CGPS), by investigating three levels of context clues (i. e., detection, memory and scene) in unconstrained natural images.

Pedestrian Detection Person Re-Identification +1

Context-Aware Image Inpainting with Learned Semantic Priors

1 code implementation14 Jun 2021 Wendong Zhang, Junwei Zhu, Ying Tai, Yunbo Wang, Wenqing Chu, Bingbing Ni, Chengjie Wang, Xiaokang Yang

Based on the semantic priors, we further propose a context-aware image inpainting model, which adaptively integrates global semantics and local features in a unified image generator.

Image Inpainting Knowledge Distillation

SimSwap: An Efficient Framework For High Fidelity Face Swapping

2 code implementations11 Jun 2021 Renwang Chen, Xuanhong Chen, Bingbing Ni, Yanhao Ge

In contrast to previous approaches that either lack the ability to generalize to arbitrary identity or fail to preserve attributes like facial expression and gaze direction, our framework is capable of transferring the identity of an arbitrary source face into an arbitrary target face while preserving the attributes of the target face.

 Ranked #1 on Face Swapping on FaceForensics++ (ID retrieval metric)

Face Swapping

Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement

no code implementations CVPR 2021 Zefan Li, Chenxi Liu, Alan Yuille, Bingbing Ni, Wenjun Zhang, Wen Gao

For a given unsupervised task, we design multilevel tasks and define different learning stages for the deep network.

Self-supervised Graph-level Representation Learning with Local and Global Structure

1 code implementation8 Jun 2021 Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang

This paper studies unsupervised/self-supervised whole-graph representation learning, which is critical in many tasks such as molecule properties prediction in drug and material discovery.

Graph Representation Learning

X-volution: On the unification of convolution and self-attention

no code implementations4 Jun 2021 Xuanhong Chen, Hang Wang, Bingbing Ni

Convolution and self-attention are acting as two fundamental building blocks in deep neural networks, where the former extracts local image features in a linear way while the latter non-locally encodes high-order contextual relationships.

Image Classification Instance Segmentation +1

3D Human Action Representation Learning via Cross-View Consistency Pursuit

1 code implementation CVPR 2021 Linguo Li, Minsi Wang, Bingbing Ni, Hang Wang, Jiancheng Yang, Wenjun Zhang

In this work, we propose a Cross-view Contrastive Learning framework for unsupervised 3D skeleton-based action Representation (CrosSCLR), by leveraging multi-view complementary supervision signal.

Action Recognition Contrastive Learning +1

Learning Multi-Attention Context Graph for Group-Based Re-Identification

1 code implementation29 Apr 2021 Yichao Yan, Jie Qin, Bingbing Ni, Jiaxin Chen, Li Liu, Fan Zhu, Wei-Shi Zheng, Xiaokang Yang, Ling Shao

Extensive experiments on the novel dataset as well as three existing datasets clearly demonstrate the effectiveness of the proposed framework for both group-based re-id tasks.

Person Re-Identification

Graphical Modeling for Multi-Source Domain Adaptation

1 code implementation27 Apr 2021 Minghao Xu, Hang Wang, Bingbing Ni

In this problem, it is essential to utilize the labeled source data and the unlabeled target data to approach the conditional distribution of semantic label on target domain, which requires the joint modeling across different domains and also an effective domain combination scheme.

Domain Adaptation

Bilevel Online Adaptation for Out-of-Domain Human Mesh Reconstruction

1 code implementation CVPR 2021 Shanyan Guan, Jingwei Xu, Yunbo Wang, Bingbing Ni, Xiaokang Yang

This paper considers a new problem of adapting a pre-trained model of human mesh reconstruction to out-of-domain streaming videos.

3D Human Pose Estimation

GraphSAD: Learning Graph Representations with Structure-Attribute Disentanglement

no code implementations1 Jan 2021 Minghao Xu, Hang Wang, Bingbing Ni, Wenjun Zhang, Jian Tang

We propose to disentangle graph structure and node attributes into two distinct sets of representations, and such disentanglement can be done in either the input or the embedding space.

Graph Classification

Image Translation via Fine-grained Knowledge Transfer

1 code implementation21 Dec 2020 Xuanhong Chen, Ziang Liu, Ting Qiu, Bingbing Ni, Naiyuan Liu, XiWei Hu, Yuhan Li

Extensive experiments well demonstrate the effectiveness and feasibility of our framework in different image-translation tasks.

Style Transfer Transfer Learning

RainNet: A Large-Scale Dataset for Spatial Precipitation Downscaling

1 code implementation17 Dec 2020 Xuanhong Chen, Kairui Feng, Naiyuan Liu, Yifan Lu, Zhengyan Tong, Bingbing Ni, Ziang Liu, Ning Lin

In order to facilitate the research on precipitation downscaling for deep learning, we present the first REAL (non-simulated) Large-Scale Spatial Precipitation Downscaling Dataset, RainNet, which contains 62, 424 pairs of low-resolution and high-resolution precipitation maps for 17 years.

Sketch Generation with Drawing Process Guided by Vector Flow and Grayscale

1 code implementation16 Dec 2020 Zhengyan Tong, Xuanhong Chen, Bingbing Ni, Xiaohang Wang

Existing pencil sketch algorithms are based on texture rendering rather than the direct imitation of strokes, making them unable to show the drawing process but only a final result.

Omni-GAN: On the Secrets of cGANs and Beyond

1 code implementation26 Nov 2020 Peng Zhou, Lingxi Xie, Bingbing Ni, Cong Geng, Qi Tian

The conditional generative adversarial network (cGAN) is a powerful tool of generating high-quality images, but existing approaches mostly suffer unsatisfying performance or the risk of mode collapse.

Conditional Image Generation

CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute Editing

no code implementations ECCV 2020 Xuanhong Chen, Bingbing Ni, Naiyuan Liu, Ziang Liu, Yiliu Jiang, Loc Truong, Qi Tian

In contrast to great success of memory-consuming face editing methods at a low resolution, to manipulate high-resolution (HR) facial images, i. e., typically larger than 7682 pixels, with very limited memory is still challenging.

Image Generation

Learning Black-Box Attackers with Transferable Priors and Query Feedback

1 code implementation NeurIPS 2020 Jiancheng Yang, Yangzhou Jiang, Xiaoyang Huang, Bingbing Ni, Chenglong Zhao

This paper addresses the challenging black-box adversarial attack problem, where only classification confidence of a victim model is available.

Adversarial Attack

Anisotropic Stroke Control for Multiple Artists Style Transfer

1 code implementation16 Oct 2020 Xuanhong Chen, Xirui Yan, Naiyuan Liu, Ting Qiu, Bingbing Ni

Furthermore, the results are with distinctive artistic style and retain the anisotropic semantic information.

Style Transfer

Hierarchical Classification of Pulmonary Lesions: A Large-Scale Radio-Pathomics Study

no code implementations8 Oct 2020 Jiancheng Yang, Mingze Gao, Kaiming Kuang, Bingbing Ni, Yunlang She, Dong Xie, Chang Chen

A three-level hierarchical classification system for pulmonary lesions is developed, which covers most diseases in cancer-related diagnosis.

Classification Computed Tomography (CT) +3

MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response

1 code implementation8 Oct 2020 Jiancheng Yang, Jiajun Chen, Kaiming Kuang, Tiancheng Lin, Junjun He, Bingbing Ni

Furthermore, we experiment the proposed method on an in-house, retrospective dataset of real-world non-small cell lung cancer patients under anti-PD-1 immunotherapy.

Time Series Time Series Classification

Hierarchical Style-based Networks for Motion Synthesis

no code implementations ECCV 2020 Jingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Xiaolong Wang, Trevor Darrell

Generating diverse and natural human motion is one of the long-standing goals for creating intelligent characters in the animated world.

motion synthesis

Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation

1 code implementation ECCV 2020 Hang Wang, Minghao Xu, Bingbing Ni, Wenjun Zhang

Transferring knowledges learned from multiple source domains to target domain is a more practical and challenging task than conventional single-source domain adaptation.

Domain Adaptation Multi-Source Unsupervised Domain Adaptation

Collaborative Learning for Faster StyleGAN Embedding

no code implementations3 Jul 2020 Shanyan Guan, Ying Tai, Bingbing Ni, Feida Zhu, Feiyue Huang, Xiaokang Yang

The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator.

Video Prediction via Example Guidance

1 code implementation ICML 2020 Jingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Trevor Darrell

In video prediction tasks, one major challenge is to capture the multi-modal nature of future contents and dynamics.

Video Prediction

Searching towards Class-Aware Generators for Conditional Generative Adversarial Networks

1 code implementation25 Jun 2020 Peng Zhou, Lingxi Xie, Xiaopeng Zhang, Bingbing Ni, Qi Tian

To learn the sampling policy, a Markov decision process is embedded into the search algorithm and a moving average is applied for better stability.

Image Generation

AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes

1 code implementation5 May 2020 Jiancheng Yang, Yi He, Xiaoyang Huang, Jingwei Xu, Xiaodan Ye, Guangyu Tao, Bingbing Ni

This paper addresses a fundamental challenge in 3D medical image processing: how to deal with imaging thickness.

Representation Learning

Relational Learning between Multiple Pulmonary Nodules via Deep Set Attention Transformers

no code implementations12 Apr 2020 Jiancheng Yang, Haoran Deng, Xiaoyang Huang, Bingbing Ni, Yi Xu

In this study, we propose a multiple instance learning (MIL) approach and empirically prove the benefit to learn the relations between multiple nodules.

Multiple Instance Learning Relational Reasoning

Cross-domain Detection via Graph-induced Prototype Alignment

1 code implementation CVPR 2020 Minghao Xu, Hang Wang, Bingbing Ni, Qi Tian, Wenjun Zhang

To mitigate these problems, we propose a Graph-induced Prototype Alignment (GPA) framework to seek for category-level domain alignment via elaborate prototype representations.

Domain Adaptation Object Detection

Wasserstein-Bounded Generative Adversarial Networks

no code implementations ICLR 2020 Peng Zhou, Bingbing Ni, Lingxi Xie, Xiaopeng Zhang, Hang Wang, Cong Geng, Qi Tian

In the field of Generative Adversarial Networks (GANs), how to design a stable training strategy remains an open problem.

Adversarial Domain Adaptation with Domain Mixup

1 code implementation4 Dec 2019 Minghao Xu, Jian Zhang, Bingbing Ni, Teng Li, Chengjie Wang, Qi Tian, Wenjun Zhang

In this paper, we present adversarial domain adaptation with domain mixup (DM-ADA), which guarantees domain-invariance in a more continuous latent space and guides the domain discriminator in judging samples' difference relative to source and target domains.

Domain Adaptation

Reinventing 2D Convolutions for 3D Images

2 code implementations24 Nov 2019 Jiancheng Yang, Xiaoyang Huang, Yi He, Jingwei Xu, Canqian Yang, Guozheng Xu, Bingbing Ni

Theoretically, ANY 2D CNN (ResNet, DenseNet, or DeepLab) is able to be converted into a 3D ACS CNN, with pretrained weight of a same parameter size.

Representation Learning

CartoonRenderer: An Instance-based Multi-Style Cartoon Image Translator

no code implementations14 Nov 2019 Yugang Chen, Muchun Chen, Chaoyue Song, Bingbing Ni

In a nutshell, our method maps photo into a feature model and renders the feature model back into image space.

Image Stylization

Facial Image Deformation Based on Landmark Detection

no code implementations30 Oct 2019 Chaoyue Song, Yugang Chen, Shulai Zhang, Bingbing Ni

In this work, we use facial landmarks to make the deformation for facial images more authentic.

Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis

no code implementations20 Oct 2019 Jiancheng Yang, Rongyao Fang, Bingbing Ni, Yamin Li, Yi Xu, Linguo Li

The final diagnosis is obtained by combining the ambiguity prior sample and lesion representation, and the whole network named $DenseSharp^{+}$ is end-to-end trainable.

Probabilistic Deep Learning

Evaluating and Boosting Uncertainty Quantification in Classification

no code implementations13 Sep 2019 Xiaoyang Huang, Jiancheng Yang, Linguo Li, Haoran Deng, Bingbing Ni, Yi Xu

Emergence of artificial intelligence techniques in biomedical applications urges the researchers to pay more attention on the uncertainty quantification (UQ) in machine-assisted medical decision making.

Classification Decision Making +1

Exploiting Channel Similarity for Accelerating Deep Convolutional Neural Networks

no code implementations6 Aug 2019 Yunxiang Zhang, Chenglong Zhao, Bingbing Ni, Jian Zhang, Haoran Deng

To address the limitations of existing magnitude-based pruning algorithms in cases where model weights or activations are of large and similar magnitude, we propose a novel perspective to discover parameter redundancy among channels and accelerate deep CNNs via channel pruning.

Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling

no code implementations CVPR 2019 Jiancheng Yang, Qiang Zhang, Bingbing Ni, Linguo Li, Jinxian Liu, Mengdie Zhou, Qi Tian

Thereby, we for the first time propose an end-to-end learnable and task-agnostic sampling operation, named Gumbel Subset Sampling (GSS), to select a representative subset of input points.

Adversarial Attack and Defense on Point Sets

no code implementations28 Feb 2019 Jiancheng Yang, Qiang Zhang, Rongyao Fang, Bingbing Ni, Jinxian Liu, Qi Tian

A set of novel 3D point cloud attack operations are proposed via pointwise gradient perturbation and adversarial point attachment / detachment.

Adversarial Attack

Disentangled Deep Autoencoding Regularization for Robust Image Classification

no code implementations27 Feb 2019 Zhenyu Duan, Martin Renqiang Min, Li Erran Li, Mingbo Cai, Yi Xu, Bingbing Ni

In spite of achieving revolutionary successes in machine learning, deep convolutional neural networks have been recently found to be vulnerable to adversarial attacks and difficult to generalize to novel test images with reasonably large geometric transformations.

Classification General Classification +2

Video Prediction via Selective Sampling

1 code implementation NeurIPS 2018 Jingwei Xu, Bingbing Ni, Xiaokang Yang

Most adversarial learning based video prediction methods suffer from image blur, since the commonly used adversarial and regression loss pair work rather in a competitive way than collaboration, yielding compromised blur effect.

Video Prediction

Deep Regression Tracking with Shrinkage Loss

1 code implementation ECCV 2018 Xiankai Lu, Chao Ma, Bingbing Ni, Xiaokang Yang, Ian Reid, Ming-Hsuan Yang

Regression trackers directly learn a mapping from regularly dense samples of target objects to soft labels, which are usually generated by a Gaussian function, to estimate target positions.

Geometric Constrained Joint Lane Segmentation and Lane Boundary Detection

no code implementations ECCV 2018 Jie Zhang, Yi Xu, Bingbing Ni, Zhenyu Duan

The main contributions of the proposed frame- work are highlighted in two facets: (1) We put forward a multiple-task learning framework with mutually interlinked sub-structures between lane segmentation and lane boundary detection to improve overall performance.

Boundary Detection Lane Detection

Egocentric Activity Prediction via Event Modulated Attention

no code implementations ECCV 2018 Yang Shen, Bingbing Ni, Zefan Li, Ning Zhuang

Predicting future activities from an egocentric viewpoint is of particular interest in assisted living.

Activity Prediction Event Extraction

Structure Preserving Video Prediction

no code implementations CVPR 2018 Jingwei Xu, Bingbing Ni, Zefan Li, Shuo Cheng, Xiaokang Yang

Despite recent emergence of adversarial based methods for video prediction, existing algorithms often produce unsatisfied results in image regions with rich structural information (i. e., object boundary) and detailed motion (i. e., articulated body movement).

Video Prediction

Multiple Granularity Group Interaction Prediction

no code implementations CVPR 2018 Taiping Yao, Minsi Wang, Bingbing Ni, Huawei Wei, Xiaokang Yang

Most human activity analysis works (i. e., recognition or prediction) only focus on a single granularity, i. e., either modelling global motion based on the coarse level movement such as human trajectories or forecasting future detailed action based on body parts’ movement such as skeleton motion.

Crowd Counting via Adversarial Cross-Scale Consistency Pursuit

1 code implementation CVPR 2018 Zan Shen, Yi Xu, Bingbing Ni, Minsi Wang, Jianguo Hu, Xiaokang Yang

Crowd counting or density estimation is a challenging task in computer vision due to large scale variations, perspective distortions and serious occlusions, etc.

Crowd Counting Density Estimation

Fine-Grained Video Captioning for Sports Narrative

no code implementations CVPR 2018 Huanyu Yu, Shuo Cheng, Bingbing Ni, Minsi Wang, Jian Zhang, Xiaokang Yang

First, to facilitate this novel research of fine-grained video caption, we collected a novel dataset called Fine-grained Sports Narrative dataset (FSN) that contains 2K sports videos with ground-truth narratives from YouTube. com.

Video Captioning

Pose Transferrable Person Re-Identification

no code implementations CVPR 2018 Jinxian Liu, Bingbing Ni, Yichao Yan, Peng Zhou, Shuo Cheng, Jianguo Hu

On the other hand, in addition to the conventional discriminator of GAN (i. e., to distinguish between REAL/FAKE samples), we propose a novel guider sub-network which encourages the generated sample (i. e., with novel pose) towards better satisfying the ReID loss (i. e., cross-entropy ReID loss, triplet ReID loss).

Person Re-Identification

Flexible Network Binarization with Layer-wise Priority

no code implementations13 Sep 2017 Lixue Zhuang, Yi Xu, Bingbing Ni, Hongteng Xu

In this work, we reveal an important fact that binarizing different layers has a widely-varied effect on the compression ratio of network and the loss of performance.

Binarization Pedestrian Detection

Recurrent Modeling of Interaction Context for Collective Activity Recognition

no code implementations CVPR 2017 Minsi Wang, Bingbing Ni, Xiaokang Yang

However, most of the previous activity recognition methods do not offer a flexible and scalable scheme to handle the high order context modeling problem.

Group Activity Recognition

Binary Coding for Partial Action Analysis With Limited Observation Ratios

no code implementations CVPR 2017 Jie Qin, Li Liu, Ling Shao, Bingbing Ni, Chen Chen, Fumin Shen, Yunhong Wang

Extensive experiments on four realistic action datasets in terms of three tasks (i. e., partial action retrieval, recognition and prediction) clearly show the superiority of PRBC over the state-of-the-art methods, along with significantly reduced memory load and computational costs during the online test.

Action Recognition Binarization

Image Matching via Loopy RNN

no code implementations10 Jun 2017 Donghao Luo, Bingbing Ni, Yichao Yan, Xiaokang Yang

Towards this end, we propose a novel loopy recurrent neural network (Loopy RNN), which is capable of aggregating relationship information of two input images in a progressive/iterative manner and outputting the consolidated matching score in the final iteration.

Depth Structure Preserving Scene Image Generation

no code implementations1 Jun 2017 Wendong Zhang, Bingbing Ni, Yichao Yan, Jingwei Xu, Xiaokang Yang

Key to automatically generate natural scene images is to properly arrange among various spatial elements, especially in the depth direction.

Image Generation Scene Generation

Predicting Human Interaction via Relative Attention Model

no code implementations26 May 2017 Yichao Yan, Bingbing Ni, Xiaokang Yang

Predicting human interaction is challenging as the on-going activity has to be inferred based on a partially observed video.

Person Re-Identification via Recurrent Feature Aggregation

1 code implementation23 Jan 2017 Yichao Yan, Bingbing Ni, Zhichao Song, Chao Ma, Yan Yan, Xiaokang Yang

We address the person re-identification problem by effectively exploiting a globally discriminative feature representation from a sequence of tracked human regions/patches.

Patch Matching Person Re-Identification

Cascaded Interactional Targeting Network for Egocentric Video Analysis

no code implementations CVPR 2016 Yang Zhou, Bingbing Ni, Richang Hong, Xiaokang Yang, Qi Tian

Firstly, a novel EM-like learning framework is proposed to train the pixel-level deep convolutional neural network (DCNN) by seamlessly integrating weakly supervised data (i. e., massive bounding box annotations) with a small set of strongly supervised data (i. e., fully annotated hand segmentation maps) to achieve state-of-the-art hand segmentation performance.

Action Recognition Hand Segmentation

Progressively Parsing Interactional Objects for Fine Grained Action Detection

no code implementations CVPR 2016 Bingbing Ni, Xiaokang Yang, Shenghua Gao

Fine grained video action analysis often requires reliable detection and tracking of various interacting objects and human body parts, denoted as interactional object parsing.

Action Recognition Fine-Grained Action Detection +1

Manipulated Object Proposal: A Discriminative Object Extraction and Feature Fusion Framework for First-Person Daily Activity Recognition

no code implementations2 Sep 2015 Changzhi Luo, Bingbing Ni, Jun Yuan, Jian-Feng Wang, Shuicheng Yan, Meng Wang

This scheme leverages motion cues such as motion boundary and motion magnitude (in contrast, camera motion is usually considered as "noise" for most previous methods) to generate a more compact and discriminative set of object proposals, which are more closely related to the objects which are being manipulated.

Action Recognition Object Proposal Generation

Motion Part Regularization: Improving Action Recognition via Trajectory Selection

no code implementations CVPR 2015 Bingbing Ni, Pierre Moulin, Xiaokang Yang, Shuicheng Yan

Inspired by the recent advance in sentence regularization for text classification, we introduce a Motion Part Regularization framework to mining discriminative semi-local groups of dense trajectories.

Action Recognition Text Classification

Interaction Part Mining: A Mid-Level Approach for Fine-Grained Action Recognition

no code implementations CVPR 2015 Yang Zhou, Bingbing Ni, Richang Hong, Meng Wang, Qi Tian

Secondly, these object regions are matched and tracked across frames to form a large spatio-temporal graph based on the appearance matching and the dense motion trajectories through them.

Fine-grained Action Recognition Human-Object Interaction Detection

Crowded Scene Analysis: A Survey

no code implementations6 Feb 2015 Teng Li, Huan Chang, Meng Wang, Bingbing Ni, Richang Hong, Shuicheng Yan

Then, existing models, popular algorithms, evaluation protocols, as well as system performance are provided corresponding to different aspects of crowded scene analysis.

Anomaly Detection

CNN: Single-label to Multi-label

no code implementations22 Jun 2014 Yunchao Wei, Wei Xia, Junshi Huang, Bingbing Ni, Jian Dong, Yao Zhao, Shuicheng Yan

Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks.

Image Classification

Multiple Granularity Analysis for Fine-grained Action Detection

no code implementations CVPR 2014 Bingbing Ni, Vignesh R. Paramathayalan, Pierre Moulin

We propose to decompose the fine-grained human activity analysis problem into two sequential tasks with increasing granularity.

Fine-Grained Action Detection

Beta Process Multiple Kernel Learning

no code implementations CVPR 2014 Bingbing Ni, Teng Li, Pierre Moulin

Specifically, for the kernel representation calculated for each input feature instance, we multiply it element-wise with a latent binary vector named as instance selection variables, which targets at selecting good instances and attenuate the effect of ambiguous ones in the resulting new kernel representation.

Variational Inference

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