Search Results for author: Bingbing Ni

Found 122 papers, 53 papers with code

Real-Time Neural BRDF with Spherically Distributed Primitives

no code implementations12 Oct 2023 Yishun Dou, Zhong Zheng, Qiaoqiao Jin, Bingbing Ni, Yugang Chen, Junxiang Ke

We propose a novel compact and efficient neural BRDF offering highly versatile material representation, yet with very-light memory and neural computation consumption towards achieving real-time rendering.

SieveNet: Selecting Point-Based Features for Mesh Networks

no code implementations24 Aug 2023 Shengchao Yuan, Yishun Dou, Rui Shi, Bingbing Ni, Zhong Zheng

Meshes are widely used in 3D computer vision and graphics, but their irregular topology poses challenges in applying them to existing neural network architectures.

Feature Engineering

FocalDreamer: Text-driven 3D Editing via Focal-fusion Assembly

no code implementations21 Aug 2023 Yuhan Li, Yishun Dou, Yue Shi, Yu Lei, Xuanhong Chen, Yi Zhang, Peng Zhou, Bingbing Ni

While text-3D editing has made significant strides in leveraging score distillation sampling, emerging approaches still fall short in delivering separable, precise and consistent outcomes that are vital to content creation.

Omni Aggregation Networks for Lightweight Image Super-Resolution

1 code implementation CVPR 2023 Hang Wang, Xuanhong Chen, Bingbing Ni, Yutian Liu, Jinfan Liu

While lightweight ViT framework has made tremendous progress in image super-resolution, its uni-dimensional self-attention modeling, as well as homogeneous aggregation scheme, limit its effective receptive field (ERF) to include more comprehensive interactions from both spatial and channel dimensions.

Image Super-Resolution

Inferring Fluid Dynamics via Inverse Rendering

no code implementations10 Apr 2023 Jinxian Liu, Ye Chen, Bingbing Ni, Jiyao Mao, Zhenbo Yu

Humans have a strong intuitive understanding of physical processes such as fluid falling by just a glimpse of such a scene picture, i. e., quickly derived from our immersive visual experiences in memory.

Inverse Rendering

3DQD: Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process

1 code implementation18 Mar 2023 Yuhan Li, Yishun Dou, Xuanhong Chen, Bingbing Ni, Yilin Sun, Yutian Liu, Fuzhen Wang

We develop a generalized 3D shape generation prior model, tailored for multiple 3D tasks including unconditional shape generation, point cloud completion, and cross-modality shape generation, etc.

3D Shape Generation Point Cloud Completion

Frequency-Modulated Point Cloud Rendering with Easy Editing

1 code implementation CVPR 2023 Yi Zhang, Xiaoyang Huang, Bingbing Ni, Teng Li, Wenjun Zhang

We develop an effective point cloud rendering pipeline for novel view synthesis, which enables high fidelity local detail reconstruction, real-time rendering and user-friendly editing.

Novel View Synthesis SSIM

USR: Unsupervised Separated 3D Garment and Human Reconstruction via Geometry and Semantic Consistency

no code implementations21 Feb 2023 Yue Shi, Yuxuan Xiong, Jingyi Chai, Bingbing Ni, Wenjun Zhang

To address these issues, we propose an unsupervised separated 3D garments and human reconstruction model (USR), which reconstructs the human body and authentic textured clothes in layers without 3D models.

Virtual Try-on

AudioEar: Single-View Ear Reconstruction for Personalized Spatial Audio

1 code implementation30 Jan 2023 Xiaoyang Huang, Yanjun Wang, Yang Liu, Bingbing Ni, Wenjun Zhang, Jinxian Liu, Teng Li

To this end, we propose to achieve personalized spatial audio by reconstructing 3D human ears with single-view images.

Depth Estimation

Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process

1 code implementation CVPR 2023 Yuhan Li, Yishun Dou, Xuanhong Chen, Bingbing Ni, Yilin Sun, Yutian Liu, Fuzhen Wang

We develop a generalized 3D shape generation prior model, tailored for multiple 3D tasks including unconditional shape generation, point cloud completion, and cross-modality shape generation, etc.

3D Shape Generation Point Cloud Completion

Editable Image Geometric Abstraction via Neural Primitive Assembly

no code implementations ICCV 2023 Ye Chen, Bingbing Ni, Xuanhong Chen, Zhangli Hu

This work explores a novel image geometric abstraction paradigm based on assembly out of a pool of pre-defined simple parametric primitives (i. e., triangle, rectangle, circle and semicircle), facilitating controllable shape editing in images.

Graph Matching

Exploring and Utilizing Pattern Imbalance

no code implementations CVPR 2023 Shibin Mei, Chenglong Zhao, Shengchao Yuan, Bingbing Ni

In this paper, we identify pattern imbalance from several aspects, and further develop a new training scheme to avert pattern preference as well as spurious correlation.

Domain Generalization

Learning Shape Primitives via Implicit Convexity Regularization

1 code implementation ICCV 2023 Xiaoyang Huang, Yi Zhang, Kai Chen, Teng Li, Wenjun Zhang, Bingbing Ni

In this work, a novel regularization term named Implicit Convexity Regularization (ICR) imposed on implicit primitive learning is proposed to tackle this problem.

Multiplicative Fourier Level of Detail

no code implementations CVPR 2023 Yishun Dou, Zhong Zheng, Qiaoqiao Jin, Bingbing Ni

We develop a simple yet surprisingly effective implicit representing scheme called Multiplicative Fourier Level of Detail (MFLOD) motivated by the recent success of multiplicative filter network.

3D Shape Representation Representation Learning

GARF:Geometry-Aware Generalized Neural Radiance Field

no code implementations5 Dec 2022 Yue Shi, Dingyi Rong, Bingbing Ni, Chang Chen, Wenjun Zhang

To address these issues, we propose Geometry-Aware Generalized Neural Radiance Field (GARF) with a geometry-aware dynamic sampling (GADS) strategy to perform real-time novel view rendering and unsupervised depth estimation on unseen scenes without per-scene optimization.

Depth Estimation Novel View Synthesis +1

Boosting Point Clouds Rendering via Radiance Mapping

1 code implementation27 Oct 2022 Xiaoyang Huang, Yi Zhang, Bingbing Ni, Teng Li, Kai Chen, Wenjun Zhang

In this work, we focus on boosting the image quality of point clouds rendering with a compact model design.

RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline Extraction

1 code implementation18 Oct 2022 Liang Jin, Shixuan Gu, Donglai Wei, Jason Ken Adhinarta, Kaiming Kuang, Yongjie Jessica Zhang, Hanspeter Pfister, Bingbing Ni, Jiancheng Yang, Ming Li

Based on the RibSeg v2, we develop a pipeline including deep learning-based methods for rib labeling, and a skeletonization-based method for centerline extraction.

Computational Efficiency Segmentation

Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweening

1 code implementation9 Oct 2022 Yunhao Li, Zhenbo Yu, Yucheng Zhu, Bingbing Ni, Guangtao Zhai, Wei Shen

Stage I introduces a test time adaptation strategy, which improves the physical plausibility of synthesized human skeleton motions by optimizing skeleton joint locations.

Motion Synthesis Reinforcement Learning (RL) +1

Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis

1 code implementation30 Jun 2022 Jiancheng Yang, Rui Shi, Udaranga Wickramasinghe, Qikui Zhu, Bingbing Ni, Pascal Fua

Besides, we develop a new Adrenal gLand ANalysis (ALAN) dataset with the proposed NeAR, where each case consists of a 3D shape of adrenal gland and its diagnosis label (normal vs. abnormal) assigned by experts.

Differentiable Projection from Optical Coherence Tomography B-Scan without Retinal Layer Segmentation Supervision

1 code implementation11 Jun 2022 Dingyi Rong, Jiancheng Yang, Bingbing Ni, Bilian Ke

Projection map (PM) from optical coherence tomography (OCT) B-scan is an important tool to diagnose retinal diseases, which typically requires retinal layer segmentation.

Segmentation

HIRL: A General Framework for Hierarchical Image Representation Learning

1 code implementation26 May 2022 Minghao Xu, Yuanfan Guo, Xuanyu Zhu, Jiawen Li, Zhenbang Sun, Jian Tang, Yi Xu, Bingbing Ni

This framework aims to learn multiple semantic representations for each image, and these representations are structured to encode image semantics from fine-grained to coarse-grained.

Image Clustering Representation Learning +3

Representation-Agnostic Shape Fields

1 code implementation ICLR 2022 Xiaoyang Huang, Jiancheng Yang, Yanjun Wang, Ziyu Chen, Linguo Li, Teng Li, Bingbing Ni, Wenjun Zhang

In this study, we present Representation-Agnostic Shape Fields (RASF), a generalizable and computation-efficient shape embedding module for 3D deep learning.

Gradient Correction beyond Gradient Descent

no code implementations16 Mar 2022 Zefan Li, Bingbing Ni, Teng Li, Wenjun Zhang, Wen Gao

GCGD consists of two plug-in modules: 1) inspired by the idea of gradient prediction, we propose a \textbf{GC-W} module for weight gradient correction; 2) based on Neural ODE, we propose a \textbf{GC-ODE} module for hidden states gradient correction.

HCSC: Hierarchical Contrastive Selective Coding

2 code implementations CVPR 2022 Yuanfan Guo, Minghao Xu, Jiawen Li, Bingbing Ni, Xuanyu Zhu, Zhenbang Sun, Yi Xu

In this framework, a set of hierarchical prototypes are constructed and also dynamically updated to represent the hierarchical semantic structures underlying the data in the latent space.

Contrastive Learning Representation Learning

Contrastive Regression for Domain Adaptation on Gaze Estimation

no code implementations CVPR 2022 Yaoming Wang, Yangzhou Jiang, Jin Li, Bingbing Ni, Wenrui Dai, Chenglin Li, Hongkai Xiong, Teng Li

Appearance-based Gaze Estimation leverages deep neural networks to regress the gaze direction from monocular images and achieve impressive performance.

Domain Generalization Gaze Estimation +1

ImplicitAtlas: Learning Deformable Shape Templates in Medical Imaging

no code implementations CVPR 2022 Jiancheng Yang, Udaranga Wickramasinghe, Bingbing Ni, Pascal Fua

Deep implicit shape models have become popular in the computer vision community at large but less so for biomedical applications.

MovieNet-PS: A Large-Scale Person Search Dataset in the Wild

1 code implementation5 Dec 2021 Jie Qin, Peng Zheng, Yichao Yan, Rong Quan, Xiaogang Cheng, Bingbing Ni

Person search aims to jointly localize and identify a query person from natural, uncropped images, which has been actively studied over the past few years.

Person Search

Joint Modeling of Visual Objects and Relations for Scene Graph Generation

no code implementations NeurIPS 2021 Minghao Xu, Meng Qu, Bingbing Ni, Jian Tang

We further propose an efficient and effective algorithm for inference based on mean-field variational inference, in which we first provide a warm initialization by independently predicting the objects and their relations according to the current model, followed by a few iterations of relational reasoning.

Graph Generation Knowledge Graph Embedding +5

TAL: Two-stream Adaptive Learning for Generalizable Person Re-identification

no code implementations29 Nov 2021 Yichao Yan, Junjie Li, Shengcai Liao, Jie Qin, Bingbing Ni, Xiaokang Yang

In the meantime, we design an adaptive BN layer in the domain-invariant stream, to approximate the statistics of various unseen domains.

Domain Generalization Generalizable Person Re-identification +1

Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation

1 code implementation7 Nov 2021 Shanyan Guan, Jingwei Xu, Michelle Z. He, Yunbo Wang, Bingbing Ni, Xiaokang Yang

We consider a new problem of adapting a human mesh reconstruction model to out-of-domain streaming videos, where performance of existing SMPL-based models are significantly affected by the distribution shift represented by different camera parameters, bone lengths, backgrounds, and occlusions.

3D Absolute Human Pose Estimation Bilevel Optimization

MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification

3 code implementations27 Oct 2021 Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bilian Ke, Hanspeter Pfister, Bingbing Ni

We introduce MedMNIST v2, a large-scale MNIST-like dataset collection of standardized biomedical images, including 12 datasets for 2D and 6 datasets for 3D.

AutoML Image Classification

CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis

1 code implementation19 Oct 2021 Peng Zhou, Lingxi Xie, Bingbing Ni, Qi Tian

The style-based GAN (StyleGAN) architecture achieved state-of-the-art results for generating high-quality images, but it lacks explicit and precise control over camera poses.

3D-Aware Image Synthesis Transfer Learning

Asymmetric 3D Context Fusion for Universal Lesion Detection

1 code implementation17 Sep 2021 Jiancheng Yang, Yi He, Kaiming Kuang, Zudi Lin, Hanspeter Pfister, Bingbing Ni

The proposed A3D consistently outperforms symmetric context fusion operators by considerable margins, and establishes a new \emph{state of the art} on DeepLesion.

Computed Tomography (CT) Lesion Detection +1

RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans

1 code implementation17 Sep 2021 Jiancheng Yang, Shixuan Gu, Donglai Wei, Hanspeter Pfister, Bingbing Ni

Manual rib inspections in computed tomography (CT) scans are clinically critical but labor-intensive, as 24 ribs are typically elongated and oblique in 3D volumes.

Computed Tomography (CT) Segmentation

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

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.

Face Swapping Vocal Bursts Intensity Prediction

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

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

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

Graphical Modeling for Multi-Source Domain Adaptation

2 code implementations27 Apr 2021 Minghao Xu, Hang Wang, Bingbing Ni

Multi-Source Domain Adaptation (MSDA) focuses on transferring the knowledge from multiple source domains to the target domain, which is a more practical and challenging problem compared to the conventional single-source domain adaptation.

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 Test

Skeleton2Mesh: Kinematics Prior Injected Unsupervised Human Mesh Recovery

no code implementations ICCV 2021 Zhenbo Yu, Junjie Wang, Jingwei Xu, Bingbing Ni, Chenglong Zhao, Minsi Wang, Wenjun Zhang

The challenges of the latter task are two folds: (1) pose failure (i. e., pose mismatching -- different skeleton definitions in dataset and SMPL , and pose ambiguity -- endpoints have arbitrary joint angle configurations for the same 3D joint coordinates).

3D Pose Estimation Human Mesh Recovery

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.

Attribute Disentanglement +1

Geometric Granularity Aware Pixel-To-Mesh

no code implementations ICCV 2021 Yue Shi, Bingbing Ni, Jinxian Liu, Dingyi Rong, Ye Qian, Wenjun Zhang

Pixel-to-mesh has wide applications, especially in virtual or augmented reality, animation and game industry.

Shape Self-Correction for Unsupervised Point Cloud Understanding

no code implementations ICCV 2021 Ye Chen, Jinxian Liu, Bingbing Ni, Hang Wang, Jiancheng Yang, Ning Liu, Teng Li, Qi Tian

Then the destroyed shape and the normal shape are sent into a point cloud network to get representations, which are employed to segment points that belong to distorted parts and further reconstruct them to restore the shape to normal.

Self-Supervised Learning

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.

Retrieval Style Transfer +2

RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling

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

To alleviate these obstacles, we present the first large-scale spatial precipitation downscaling dataset named RainNet, which contains more than $62, 400$ pairs of high-quality low/high-resolution precipitation maps for over $17$ years, ready to help the evolution of deep learning models in precipitation downscaling.

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.

Translation

Omni-GAN: On the Secrets of cGANs and Beyond

3 code implementations ICCV 2021 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 Generative Adversarial Network

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

1 code implementation 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.

Attribute Image Generation +2

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

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.

 Ranked #1 on Text-To-Speech Synthesis on 20000 utterances (using extra training data)

Text-To-Speech Synthesis Time Series +2

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.

Computed Tomography (CT) Decision Making +2

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

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 +1

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

Composable Semi-parametric Modelling for Long-range Motion Generation

no code implementations25 Sep 2019 Jingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Trevor Darrell

Learning diverse and natural behaviors is one of the longstanding goal for creating intelligent characters in the animated world.

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 +2

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.

Clustering

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.

Test

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 +3

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.

Multiple-choice Video Prediction

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

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.

regression

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

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.

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).

Object Video Prediction

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

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.

Descriptive 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 Analysis Action Recognition +4

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

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 Analysis Action Recognition +5

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 Foreground Segmentation +4

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 +2

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 Sentence +3

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 +2

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 Object +1

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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