Search Results for author: Rongrong Ji

Found 214 papers, 139 papers with code

API-Net: Robust Generative Classifier via a Single Discriminator

1 code implementation ECCV 2020 Xinshuai Dong, Hong Liu, Rongrong Ji, Liujuan Cao, Qixiang Ye, Jianzhuang Liu, Qi Tian

On the contrary, a discriminative classifier only models the conditional distribution of labels given inputs, but benefits from effective optimization owing to its succinct structure.

Robust classification

SSCGAN: Facial Attribute Editing via Style Skip Connections

no code implementations ECCV 2020 Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Rongrong Ji

Each connection extracts the style feature of the latent feature maps in the encoder and then performs a residual learning based mapping function in the global information space guided by the target attributes.

Enabling Deep Residual Networks for Weakly Supervised Object Detection

no code implementations ECCV 2020 Yunhang Shen, Rongrong Ji, Yan Wang, Zhiwei Chen, Feng Zheng, Feiyue Huang, Yunsheng Wu

Weakly supervised object detection (WSOD) has attracted extensive research attention due to its great flexibility of exploiting large-scale image-level annotation for detector training.

object-detection Weakly Supervised Object Detection

I&S-ViT: An Inclusive & Stable Method for Pushing the Limit of Post-Training ViTs Quantization

no code implementations16 Nov 2023 Yunshan Zhong, Jiawei Hu, Mingbao Lin, Mengzhao Chen, Rongrong Ji

Albeit the scalable performance of vision transformers (ViTs), the dense computational costs (training & inference) undermine their position in industrial applications.


Semi-Supervised Panoptic Narrative Grounding

1 code implementation27 Oct 2023 Danni Yang, Jiayi Ji, Xiaoshuai Sun, Haowei Wang, Yinan Li, Yiwei Ma, Rongrong Ji

Remarkably, our SS-PNG-NW+ outperforms fully-supervised models with only 30% and 50% supervision data, exceeding their performance by 0. 8% and 1. 1% respectively.

Data Augmentation Pseudo Label

NICE: Improving Panoptic Narrative Detection and Segmentation with Cascading Collaborative Learning

1 code implementation17 Oct 2023 Haowei Wang, Jiayi Ji, Tianyu Guo, Yilong Yang, Yiyi Zhou, Xiaoshuai Sun, Rongrong Ji

To address this, we introduce two cascading modules based on the barycenter of the mask, which are Coordinate Guided Aggregation (CGA) and Barycenter Driven Localization (BDL), responsible for segmentation and detection, respectively.

Segmentation Visual Grounding

JM3D & JM3D-LLM: Elevating 3D Representation with Joint Multi-modal Cues

1 code implementation14 Oct 2023 Jiayi Ji, Haowei Wang, Changli Wu, Yiwei Ma, Xiaoshuai Sun, Rongrong Ji

The rising importance of 3D representation learning, pivotal in computer vision, autonomous driving, and robotics, is evident.

Autonomous Driving Representation Learning

Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs

1 code implementation13 Oct 2023 Yuxin Zhang, Lirui Zhao, Mingbao Lin, Yunyun Sun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji

Inspired by the Dynamic Sparse Training, DSnoT minimizes the reconstruction error between the dense and sparse LLMs, in the fashion of performing iterative weight pruning-and-growing on top of sparse LLMs.

Network Pruning

AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration

1 code implementation ICCV 2023 Lijiang Li, Huixia Li, Xiawu Zheng, Jie Wu, Xuefeng Xiao, Rui Wang, Min Zheng, Xin Pan, Fei Chao, Rongrong Ji

Therefore, we propose to search the optimal time steps sequence and compressed model architecture in a unified framework to achieve effective image generation for diffusion models without any further training.

Image Generation single-image-generation

Towards Unified Token Learning for Vision-Language Tracking

1 code implementation27 Aug 2023 Yaozong Zheng, Bineng Zhong, Qihua Liang, Guorong Li, Rongrong Ji, Xianxian Li

In this paper, we present a simple, flexible and effective vision-language (VL) tracking pipeline, termed \textbf{MMTrack}, which casts VL tracking as a token generation task.

DLIP: Distilling Language-Image Pre-training

no code implementations24 Aug 2023 Huafeng Kuang, Jie Wu, Xiawu Zheng, Ming Li, Xuefeng Xiao, Rui Wang, Min Zheng, Rongrong Ji

Furthermore, DLIP succeeds in retaining more than 95% of the performance with 22. 4% parameters and 24. 8% FLOPs compared to the teacher model and accelerates inference speed by 2. 7x.

Image Captioning Knowledge Distillation +5

A Unified Framework for 3D Point Cloud Visual Grounding

1 code implementation23 Aug 2023 Haojia Lin, Yongdong Luo, Xiawu Zheng, Lijiang Li, Fei Chao, Taisong Jin, Donghao Luo, Yan Wang, Liujuan Cao, Rongrong Ji

This elaborate design enables 3DRefTR to achieve both well-performing 3DRES and 3DREC capacities with only a 6% additional latency compared to the original 3DREC model.

Referring Expression Referring Expression Comprehension +1

M3PS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization in E-commerce

no code implementations22 Aug 2023 Tao Chen, Ze Lin, Hui Li, Jiayi Ji, Yiyi Zhou, Guanbin Li, Rongrong Ji

Furthermore, we model product attributes based on both text and image modalities so that multi-modal product characteristics can be manifested in the generated summaries.

HODN: Disentangling Human-Object Feature for HOI Detection

no code implementations20 Aug 2023 Shuman Fang, Zhiwen Lin, Ke Yan, Jie Li, Xianming Lin, Rongrong Ji

However, these methods ignore the relationship among humans, objects, and interactions: 1) human features are more contributive than object ones to interaction prediction; 2) interactive information disturbs the detection of objects but helps human detection.

Human Detection Human-Object Interaction Detection +2

Continual Face Forgery Detection via Historical Distribution Preserving

no code implementations11 Aug 2023 Ke Sun, Shen Chen, Taiping Yao, Xiaoshuai Sun, Shouhong Ding, Rongrong Ji

In this paper, we focus on a novel and challenging problem: Continual Face Forgery Detection (CFFD), which aims to efficiently learn from new forgery attacks without forgetting previous ones.

Knowledge Distillation

Pseudo-label Alignment for Semi-supervised Instance Segmentation

1 code implementation ICCV 2023 Jie Hu, Chen Chen, Liujuan Cao, Shengchuan Zhang, Annan Shu, Guannan Jiang, Rongrong Ji

Through extensive experiments conducted on the COCO and Cityscapes datasets, we demonstrate that PAIS is a promising framework for semi-supervised instance segmentation, particularly in cases where labeled data is severely limited.

Instance Segmentation Pseudo Label +3

Improving Human-Object Interaction Detection via Virtual Image Learning

no code implementations4 Aug 2023 Shuman Fang, Shuai Liu, Jie Li, Guannan Jiang, Xianming Lin, Rongrong Ji

Human-Object Interaction (HOI) detection aims to understand the interactions between humans and objects, which plays a curtail role in high-level semantic understanding tasks.

Human-Object Interaction Detection

Towards General Visual-Linguistic Face Forgery Detection

no code implementations31 Jul 2023 Ke Sun, Shen Chen, Taiping Yao, Xiaoshuai Sun, Shouhong Ding, Rongrong Ji

To address this issues, in this paper, we propose a novel paradigm named Visual-Linguistic Face Forgery Detection(VLFFD), which uses fine-grained sentence-level prompts as the annotation.

Binary Classification

Systematic Investigation of Sparse Perturbed Sharpness-Aware Minimization Optimizer

1 code implementation30 Jun 2023 Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Tianshuo Xu, Xiaoshuai Sun, Tongliang Liu, Rongrong Ji, DaCheng Tao

Sharpness-Aware Minimization (SAM) is a popular solution that smooths the loss landscape by minimizing the maximized change of training loss when adding a perturbation to the weight.

Approximated Prompt Tuning for Vision-Language Pre-trained Models

no code implementations27 Jun 2023 Qiong Wu, Shubin Huang, Yiyi Zhou, Pingyang Dai, Annan Shu, Guannan Jiang, Rongrong Ji

Prompt tuning is a parameter-efficient way to deploy large-scale pre-trained models to downstream tasks by adding task-specific tokens.

Image Classification Transfer Learning

MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

2 code implementations23 Jun 2023 Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Zhenyu Qiu, Wei Lin, Jinrui Yang, Xiawu Zheng, Ke Li, Xing Sun, Rongrong Ji

Multimodal Large Language Model (MLLM) relies on the powerful LLM to perform multimodal tasks, showing amazing emergent abilities in recent studies, such as writing poems based on an image.

Benchmarking Language Modelling +3

Spatial Re-parameterization for N:M Sparsity

no code implementations9 Jun 2023 Yuxin Zhang, Mingbao Lin, Yunshan Zhong, Mengzhao Chen, Fei Chao, Rongrong Ji

This paper presents a Spatial Re-parameterization (SpRe) method for the N:M sparsity in CNNs.

STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection

1 code implementation CVPR 2023 Zhenglin Zhou, Huaxia Li, Hong Liu, Nanyang Wang, Gang Yu, Rongrong Ji

To solve this problem, we propose a Self-adapTive Ambiguity Reduction (STAR) loss by exploiting the properties of semantic ambiguity.

Face Alignment Facial Landmark Detection

Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual Prompting

1 code implementation1 Jun 2023 Shubin Huang, Qiong Wu, Yiyi Zhou, WeiJie Chen, Rongsheng Zhang, Xiaoshuai Sun, Rongrong Ji

In addition, we also experiment DVP with the recently popular adapter approach to keep the most parameters of PLMs intact when adapting to VL tasks, helping PLMs achieve a quick shift between single- and multi-modal tasks.

Transfer Learning Visual Prompting

DiffRate : Differentiable Compression Rate for Efficient Vision Transformers

1 code implementation ICCV 2023 Mengzhao Chen, Wenqi Shao, Peng Xu, Mingbao Lin, Kaipeng Zhang, Fei Chao, Rongrong Ji, Yu Qiao, Ping Luo

Token compression aims to speed up large-scale vision transformers (e. g. ViTs) by pruning (dropping) or merging tokens.

CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models

1 code implementation29 May 2023 Zhongxi Chen, Ke Sun, Xianming Lin, Rongrong Ji

Due to the stochastic sampling process of diffusion, our model is capable of sampling multiple possible predictions from the mask distribution, avoiding the problem of overconfident point estimation.

Denoising object-detection +2

MultiQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization

1 code implementation14 May 2023 Yunshan Zhong, Mingbao Lin, Yuyao Zhou, Mengzhao Chen, Yuxin Zhang, Fei Chao, Rongrong Ji

However, in this paper, we investigate existing methods and observe a significant accumulation of quantization errors caused by frequent bit-width switching of weights and activations, leading to limited performance.


Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution Networks

1 code implementation10 May 2023 Yunshan Zhong, Mingbao Lin, Jingjing Xie, Yuxin Zhang, Fei Chao, Rongrong Ji

Compared to the common iterative exhaustive search algorithm, our strategy avoids the enumeration of all possible combinations in the universal set, reducing the time complexity from exponential to linear.

Quantization Super-Resolution

Latent Feature Relation Consistency for Adversarial Robustness

1 code implementation29 Mar 2023 Xingbin Liu, Huafeng Kuang, Hong Liu, Xianming Lin, Yongjian Wu, Rongrong Ji

Deep neural networks have been applied in many computer vision tasks and achieved state-of-the-art performance.

Adversarial Robustness

X-Mesh: Towards Fast and Accurate Text-driven 3D Stylization via Dynamic Textual Guidance

1 code implementation ICCV 2023 Yiwei Ma, Xiaioqing Zhang, Xiaoshuai Sun, Jiayi Ji, Haowei Wang, Guannan Jiang, Weilin Zhuang, Rongrong Ji

Text-driven 3D stylization is a complex and crucial task in the fields of computer vision (CV) and computer graphics (CG), aimed at transforming a bare mesh to fit a target text.

CAT:Collaborative Adversarial Training

1 code implementation27 Mar 2023 Xingbin Liu, Huafeng Kuang, Xianming Lin, Yongjian Wu, Rongrong Ji

By revisiting the previous methods, we find different adversarial training methods have distinct robustness for sample instances.

Adversarial Robustness

You Only Segment Once: Towards Real-Time Panoptic Segmentation

2 code implementations CVPR 2023 Jie Hu, Linyan Huang, Tianhe Ren, Shengchuan Zhang, Rongrong Ji, Liujuan Cao

To reduce the computational overhead, we design a feature pyramid aggregator for the feature map extraction, and a separable dynamic decoder for the panoptic kernel generation.

Panoptic Segmentation Segmentation

Attention Disturbance and Dual-Path Constraint Network for Occluded Person Re-Identification

no code implementations20 Mar 2023 Jiaer Xia, Lei Tan, Pingyang Dai, Mingbo Zhao, Yongjian Wu, Rongrong Ji

Occluded person re-identification (Re-ID) aims to address the potential occlusion problem when matching occluded or holistic pedestrians from different camera views.

Person Re-Identification

Active Teacher for Semi-Supervised Object Detection

1 code implementation CVPR 2022 Peng Mi, Jianghang Lin, Yiyi Zhou, Yunhang Shen, Gen Luo, Xiaoshuai Sun, Liujuan Cao, Rongrong Fu, Qiang Xu, Rongrong Ji

In this paper, we study teacher-student learning from the perspective of data initialization and propose a novel algorithm called Active Teacher(Source code are available at: \url{https://github. com/HunterJ-Lin/ActiveTeacher}) for semi-supervised object detection (SSOD).

object-detection Object Detection +1

DistilPose: Tokenized Pose Regression with Heatmap Distillation

1 code implementation CVPR 2023 Suhang Ye, Yingyi Zhang, Jie Hu, Liujuan Cao, Shengchuan Zhang, Lei Shen, Jun Wang, Shouhong Ding, Rongrong Ji

Specifically, DistilPose maximizes the transfer of knowledge from the teacher model (heatmap-based) to the student model (regression-based) through Token-distilling Encoder (TDE) and Simulated Heatmaps.

Knowledge Distillation Pose Estimation +1

Towards End-to-end Semi-supervised Learning for One-stage Object Detection

1 code implementation22 Feb 2023 Gen Luo, Yiyi Zhou, Lei Jin, Xiaoshuai Sun, Rongrong Ji

In addition to this challenge, we also reveal two key issues in one-stage SSOD, which are low-quality pseudo-labeling and multi-task optimization conflict, respectively.

object-detection Object Detection +2

Towards Efficient Visual Adaption via Structural Re-parameterization

1 code implementation16 Feb 2023 Gen Luo, Minglang Huang, Yiyi Zhou, Xiaoshuai Sun, Guannan Jiang, Zhiyu Wang, Rongrong Ji

Experimental results show the superior performance and efficiency of RepAdapter than the state-of-the-art PETL methods.

Semantic Segmentation Transfer Learning

Bi-directional Masks for Efficient N:M Sparse Training

1 code implementation13 Feb 2023 Yuxin Zhang, Yiting Luo, Mingbao Lin, Yunshan Zhong, Jingjing Xie, Fei Chao, Rongrong Ji

We focus on addressing the dense backward propagation issue for training efficiency of N:M fine-grained sparsity that preserves at most N out of M consecutive weights and achieves practical speedups supported by the N:M sparse tensor core.

Towards Local Visual Modeling for Image Captioning

1 code implementation13 Feb 2023 Yiwei Ma, Jiayi Ji, Xiaoshuai Sun, Yiyi Zhou, Rongrong Ji

In this paper, we study the local visual modeling with grid features for image captioning, which is critical for generating accurate and detailed captions.

Image Captioning Object Recognition

Real-Time Image Demoireing on Mobile Devices

1 code implementation4 Feb 2023 Yuxin Zhang, Mingbao Lin, Xunchao Li, Han Liu, Guozhi Wang, Fei Chao, Shuai Ren, Yafei Wen, Xiaoxin Chen, Rongrong Ji

In this paper, we launch the first study on accelerating demoireing networks and propose a dynamic demoireing acceleration method (DDA) towards a real-time deployment on mobile devices.

Spectral Aware Softmax for Visible-Infrared Person Re-Identification

no code implementations3 Feb 2023 Lei Tan, Pingyang Dai, Qixiang Ye, Mingliang Xu, Yongjian Wu, Rongrong Ji

Based on the observation and analysis of SA-Softmax, we modify the SA-Softmax with the Feature Mask and Absolute-Similarity Term to alleviate the ambiguous optimization during model training.

Person Re-Identification

Exploring Invariant Representation for Visible-Infrared Person Re-Identification

no code implementations2 Feb 2023 Lei Tan, Yukang Zhang, ShengMei Shen, Yan Wang, Pingyang Dai, Xianming Lin, Yongjian Wu, Rongrong Ji

Cross-spectral person re-identification, which aims to associate identities to pedestrians across different spectra, faces a main challenge of the modality discrepancy.

Data Augmentation Person Re-Identification

RefCLIP: A Universal Teacher for Weakly Supervised Referring Expression Comprehension

no code implementations CVPR 2023 Lei Jin, Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Guannan Jiang, Annan Shu, Rongrong Ji

Based on RefCLIP, we further propose the first model-agnostic weakly supervised training scheme for existing REC models, where RefCLIP acts as a mature teacher to generate pseudo-labels for teaching common REC models.

Referring Expression Referring Expression Comprehension +2

Automatic Network Pruning via Hilbert-Schmidt Independence Criterion Lasso under Information Bottleneck Principle

1 code implementation ICCV 2023 Song Guo, Lei Zhang, Xiawu Zheng, Yan Wang, Yuchao Li, Fei Chao, Chenglin Wu, Shengchuan Zhang, Rongrong Ji

In this paper, we try to solve this problem by introducing a principled and unified framework based on Information Bottleneck (IB) theory, which further guides us to an automatic pruning approach.

Network Pruning

Discriminator-Cooperated Feature Map Distillation for GAN Compression

1 code implementation CVPR 2023 Tie Hu, Mingbao Lin, Lizhou You, Fei Chao, Rongrong Ji

In contrast to conventional pixel-to-pixel match methods in feature map distillation, our DCD utilizes teacher discriminator as a transformation to drive intermediate results of the student generator to be perceptually close to corresponding outputs of the teacher generator.

Image Generation Knowledge Distillation

SMMix: Self-Motivated Image Mixing for Vision Transformers

1 code implementation ICCV 2023 Mengzhao Chen, Mingbao Lin, Zhihang Lin, Yuxin Zhang, Fei Chao, Rongrong Ji

Due to the subtle designs of the self-motivated paradigm, our SMMix is significant in its smaller training overhead and better performance than other CutMix variants.

Exploring Content Relationships for Distilling Efficient GANs

1 code implementation21 Dec 2022 Lizhou You, Mingbao Lin, Tie Hu, Fei Chao, Rongrong Ji

This paper proposes a content relationship distillation (CRD) to tackle the over-parameterized generative adversarial networks (GANs) for the serviceability in cutting-edge devices.

Shadow Removal by High-Quality Shadow Synthesis

1 code implementation8 Dec 2022 Yunshan Zhong, Lizhou You, Yuxin Zhang, Fei Chao, Yonghong Tian, Rongrong Ji

Specifically, the encoder extracts the shadow feature of a region identity which is then paired with another region identity to serve as the generator input to synthesize a pseudo image.

Image Generation Shadow Removal +1

Self-supervised Graph Representation Learning for Black Market Account Detection

no code implementations6 Dec 2022 Zequan Xu, Lianyun Li, Hui Li, Qihang Sun, Shaofeng Hu, Rongrong Ji

This paper illustrates our BMA detection system SGRL (Self-supervised Graph Representation Learning) used in WeChat, a representative MMMA with over a billion users.

Graph Representation Learning Self-Supervised Learning

Meta Architecture for Point Cloud Analysis

1 code implementation CVPR 2023 Haojia Lin, Xiawu Zheng, Lijiang Li, Fei Chao, Shanshan Wang, Yan Wang, Yonghong Tian, Rongrong Ji

However, the lack of a unified framework to interpret those networks makes any systematic comparison, contrast, or analysis challenging, and practically limits healthy development of the field.

Exploiting the Partly Scratch-off Lottery Ticket for Quantization-Aware Training

1 code implementation12 Nov 2022 Yunshan Zhong, Gongrui Nan, Yuxin Zhang, Fei Chao, Rongrong Ji

In QAT, the contemporary experience is that all quantized weights are updated for an entire training process.


Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach

1 code implementation11 Oct 2022 Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Xiaoshuai Sun, Rongrong Ji, DaCheng Tao

One of the popular solutions is Sharpness-Aware Minimization (SAM), which smooths the loss landscape via minimizing the maximized change of training loss when adding a perturbation to the weight.

ECO-TR: Efficient Correspondences Finding Via Coarse-to-Fine Refinement

1 code implementation25 Sep 2022 Dongli Tan, Jiang-Jiang Liu, Xingyu Chen, Chao Chen, Ruixin Zhang, Yunhang Shen, Shouhong Ding, Rongrong Ji

In this paper, we propose an efficient structure named Efficient Correspondence Transformer (ECO-TR) by finding correspondences in a coarse-to-fine manner, which significantly improves the efficiency of functional correspondence model.

Outlier Detection

LAB-Net: LAB Color-Space Oriented Lightweight Network for Shadow Removal

1 code implementation27 Aug 2022 Hong Yang, Gongrui Nan, Mingbao Lin, Fei Chao, Yunhang Shen, Ke Li, Rongrong Ji

Finally, the LSA modules are further developed to fully use the prior information in non-shadow regions to cleanse the shadow regions.

Shadow Removal

CycleTrans: Learning Neutral yet Discriminative Features for Visible-Infrared Person Re-Identification

no code implementations21 Aug 2022 Qiong Wu, Jiaer Xia, Pingyang Dai, Yiyi Zhou, Yongjian Wu, Rongrong Ji

Visible-infrared person re-identification (VI-ReID) is a task of matching the same individuals across the visible and infrared modalities.

Person Re-Identification

Dynamic Prototype Mask for Occluded Person Re-Identification

1 code implementation19 Jul 2022 Lei Tan, Pingyang Dai, Rongrong Ji, Yongjian Wu

Although person re-identification has achieved an impressive improvement in recent years, the common occlusion case caused by different obstacles is still an unsettled issue in real application scenarios.

Person Re-Identification

Cycle Encoding of a StyleGAN Encoder for Improved Reconstruction and Editability

1 code implementation19 Jul 2022 Xudong Mao, Liujuan Cao, Aurele T. Gnanha, Zhenguo Yang, Qing Li, Rongrong Ji

The recently proposed pivotal tuning model makes significant progress towards reconstruction and editability, by using a two-step approach that first inverts the input image into a latent code, called pivot code, and then alters the generator so that the input image can be accurately mapped into the pivot code.

Clover: Towards A Unified Video-Language Alignment and Fusion Model

1 code implementation CVPR 2023 Jingjia Huang, Yinan Li, Jiashi Feng, Xinglong Wu, Xiaoshuai Sun, Rongrong Ji

We then introduce \textbf{Clover}\textemdash a Correlated Video-Language pre-training method\textemdash towards a universal Video-Language model for solving multiple video understanding tasks with neither performance nor efficiency compromise.

Language Modelling Question Answering +10

X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval

1 code implementation15 Jul 2022 Yiwei Ma, Guohai Xu, Xiaoshuai Sun, Ming Yan, Ji Zhang, Rongrong Ji

However, cross-grained contrast, which is the contrast between coarse-grained representations and fine-grained representations, has rarely been explored in prior research.

Contrastive Learning Retrieval +2

Learning Best Combination for Efficient N:M Sparsity

1 code implementation14 Jun 2022 Yuxin Zhang, Mingbao Lin, Zhihang Lin, Yiting Luo, Ke Li, Fei Chao, Yongjian Wu, Rongrong Ji

In this paper, we show that the N:M learning can be naturally characterized as a combinatorial problem which searches for the best combination candidate within a finite collection.

Super Vision Transformer

1 code implementation23 May 2022 Mingbao Lin, Mengzhao Chen, Yuxin Zhang, Chunhua Shen, Rongrong Ji, Liujuan Cao

Experimental results on ImageNet demonstrate that our SuperViT can considerably reduce the computational costs of ViT models with even performance increase.

Shadow-Aware Dynamic Convolution for Shadow Removal

2 code implementations10 May 2022 Yimin Xu, Mingbao Lin, Hong Yang, Fei Chao, Rongrong Ji

Inspired by the fact that the color mapping of the non-shadow region is easier to learn, our SADC processes the non-shadow region with a lightweight convolution module in a computationally cheap manner and recovers the shadow region with a more complicated convolution module to ensure the quality of image reconstruction.

Image Reconstruction Shadow Removal

A Closer Look at Branch Classifiers of Multi-exit Architectures

no code implementations28 Apr 2022 Shaohui Lin, Bo Ji, Rongrong Ji, Angela Yao

Multi-exit architectures consist of a backbone and branch classifiers that offer shortened inference pathways to reduce the run-time of deep neural networks.

A Survivor in the Era of Large-Scale Pretraining: An Empirical Study of One-Stage Referring Expression Comprehension

1 code implementation17 Apr 2022 Gen Luo, Yiyi Zhou, Jiamu Sun, Xiaoshuai Sun, Rongrong Ji

But the most encouraging finding is that with much less training overhead and parameters, SimREC can still achieve better performance than a set of large-scale pre-trained models, e. g., UNITER and VILLA, portraying the special role of REC in existing V&L research.

Data Augmentation Referring Expression +1

PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation

1 code implementation2 Apr 2022 Jing He, Yiyi Zhou, Qi Zhang, Jun Peng, Yunhang Shen, Xiaoshuai Sun, Chao Chen, Rongrong Ji

Pixel synthesis is a promising research paradigm for image generation, which can well exploit pixel-wise prior knowledge for generation.

Image Generation regression

SeqTR: A Simple yet Universal Network for Visual Grounding

2 code implementations30 Mar 2022 Chaoyang Zhu, Yiyi Zhou, Yunhang Shen, Gen Luo, Xingjia Pan, Mingbao Lin, Chao Chen, Liujuan Cao, Xiaoshuai Sun, Rongrong Ji

In this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e. g., phrase localization, referring expression comprehension (REC) and segmentation (RES).

Referring Expression Referring Expression Comprehension +1

Training-free Transformer Architecture Search

1 code implementation CVPR 2022 Qinqin Zhou, Kekai Sheng, Xiawu Zheng, Ke Li, Xing Sun, Yonghong Tian, Jie Chen, Rongrong Ji

Recently, Vision Transformer (ViT) has achieved remarkable success in several computer vision tasks.

ARM: Any-Time Super-Resolution Method

1 code implementation21 Mar 2022 Bohong Chen, Mingbao Lin, Kekai Sheng, Mengdan Zhang, Peixian Chen, Ke Li, Liujuan Cao, Rongrong Ji

To that effect, we construct an Edge-to-PSNR lookup table that maps the edge score of an image patch to the PSNR performance for each subnet, together with a set of computation costs for the subnets.

Image Super-Resolution

Global2Local: A Joint-Hierarchical Attention for Video Captioning

no code implementations13 Mar 2022 Chengpeng Dai, Fuhai Chen, Xiaoshuai Sun, Rongrong Ji, Qixiang Ye, Yongjian Wu

Recently, automatic video captioning has attracted increasing attention, where the core challenge lies in capturing the key semantic items, like objects and actions as well as their spatial-temporal correlations from the redundant frames and semantic content.

Video Captioning

Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks

1 code implementation8 Mar 2022 Yunshan Zhong, Mingbao Lin, Xunchao Li, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji

However, these methods suffer from severe performance degradation when quantizing the SR models to ultra-low precision (e. g., 2-bit and 3-bit) with the low-cost layer-wise quantizer.

Quantization Super-Resolution

CF-ViT: A General Coarse-to-Fine Method for Vision Transformer

1 code implementation8 Mar 2022 Mengzhao Chen, Mingbao Lin, Ke Li, Yunhang Shen, Yongjian Wu, Fei Chao, Rongrong Ji

Our proposed CF-ViT is motivated by two important observations in modern ViT models: (1) The coarse-grained patch splitting can locate informative regions of an input image.

Boosting Crowd Counting via Multifaceted Attention

1 code implementation CVPR 2022 Hui Lin, Zhiheng Ma, Rongrong Ji, YaoWei Wang, Xiaopeng Hong

Secondly, we design the Local Attention Regularization to supervise the training of LRA by minimizing the deviation among the attention for different feature locations.

Crowd Counting

Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters

1 code implementation15 Feb 2022 Mingbao Lin, Liujuan Cao, Yuxin Zhang, Ling Shao, Chia-Wen Lin, Rongrong Ji

Then, we introduce a recommendation-based filter selection scheme where each filter recommends a group of its closest filters.

Image Classification Network Pruning

OptG: Optimizing Gradient-driven Criteria in Network Sparsity

1 code implementation30 Jan 2022 Yuxin Zhang, Mingbao Lin, Mengzhao Chen, Fei Chao, Rongrong Ji

We prove that supermask training is to accumulate the criteria of gradient-driven sparsity for both removed and preserved weights, and it can partly solve the independence paradox.

What Hinders Perceptual Quality of PSNR-oriented Methods?

no code implementations4 Jan 2022 Tianshuo Xu, Peng Mi, Xiawu Zheng, Lijiang Li, Fei Chao, Guannan Jiang, Wei zhang, Yiyi Zhou, Rongrong Ji

E. g, in EDSR, our proposed method achieves 3. 60$\times$ faster learning speed compared to a GAN-based method with a subtle degradation in visual quality.

Contrastive Learning

Neural Architecture Search With Representation Mutual Information

1 code implementation CVPR 2022 Xiawu Zheng, Xiang Fei, Lei Zhang, Chenglin Wu, Fei Chao, Jianzhuang Liu, Wei Zeng, Yonghong Tian, Rongrong Ji

Building upon RMI, we further propose a new search algorithm termed RMI-NAS, facilitating with a theorem to guarantee the global optimal of the searched architecture.

Neural Architecture Search

DIFNet: Boosting Visual Information Flow for Image Captioning

no code implementations CVPR 2022 Mingrui Wu, Xuying Zhang, Xiaoshuai Sun, Yiyi Zhou, Chao Chen, Jiaxin Gu, Xing Sun, Rongrong Ji

Current Image captioning (IC) methods predict textual words sequentially based on the input visual information from the visual feature extractor and the partially generated sentence information.

Image Captioning

Dual Contrastive Learning for General Face Forgery Detection

no code implementations27 Dec 2021 Ke Sun, Taiping Yao, Shen Chen, Shouhong Ding, Jilin L, Rongrong Ji

With various facial manipulation techniques arising, face forgery detection has drawn growing attention due to security concerns.

Contrastive Learning

Learning to Learn Transferable Attack

1 code implementation10 Dec 2021 Shuman Fang, Jie Li, Xianming Lin, Rongrong Ji

By treating the attack of both specific data and a modified model as a task, we expect the adversarial perturbations to adopt enough tasks for generalization.

Adversarial Attack Data Augmentation +1

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization

1 code implementation CVPR 2022 Yunshan Zhong, Mingbao Lin, Gongrui Nan, Jianzhuang Liu, Baochang Zhang, Yonghong Tian, Rongrong Ji

In this paper, we observe an interesting phenomenon of intra-class heterogeneity in real data and show that existing methods fail to retain this property in their synthetic images, which causes a limited performance increase.


Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme

1 code implementation NeurIPS 2021 Shaojie Li, Jie Wu, Xuefeng Xiao, Fei Chao, Xudong Mao, Rongrong Ji

In this work, we revisit the role of discriminator in GAN compression and design a novel generator-discriminator cooperative compression scheme for GAN compression, termed GCC.

Towards Language-guided Visual Recognition via Dynamic Convolutions

1 code implementation17 Oct 2021 Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Yongjian Wu, Yue Gao, Rongrong Ji

Based on the LaConv module, we further build the first fully language-driven convolution network, termed as LaConvNet, which can unify the visual recognition and multi-modal reasoning in one forward structure.

Question Answering Referring Expression +2

Long-Range Feature Propagating for Natural Image Matting

1 code implementation25 Sep 2021 Qinglin Liu, Haozhe Xie, Shengping Zhang, Bineng Zhong, Rongrong Ji

Finally, we use the matting module which takes the image, trimap and context features to estimate the alpha matte.

Ranked #5 on Image Matting on Composition-1K (using extra training data)

Image Matting

OMPQ: Orthogonal Mixed Precision Quantization

1 code implementation16 Sep 2021 Yuexiao Ma, Taisong Jin, Xiawu Zheng, Yan Wang, Huixia Li, Yongjian Wu, Guannan Jiang, Wei zhang, Rongrong Ji

Instead of solving a problem of the original integer programming, we propose to optimize a proxy metric, the concept of network orthogonality, which is highly correlated with the loss of the integer programming but also easy to optimize with linear programming.

AutoML Quantization

Prioritized Subnet Sampling for Resource-Adaptive Supernet Training

1 code implementation12 Sep 2021 Bohong Chen, Mingbao Lin, Rongrong Ji, Liujuan Cao

At the end of training, our PSS-Net retains the best subnet in each pool to entitle a fast switch of high-quality subnets for inference when the available resources vary.

Fine-grained Data Distribution Alignment for Post-Training Quantization

1 code implementation9 Sep 2021 Yunshan Zhong, Mingbao Lin, Mengzhao Chen, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Rongrong Ji

While post-training quantization receives popularity mostly due to its evasion in accessing the original complete training dataset, its poor performance also stems from scarce images.


An Information Theory-inspired Strategy for Automatic Network Pruning

1 code implementation19 Aug 2021 Xiawu Zheng, Yuexiao Ma, Teng Xi, Gang Zhang, Errui Ding, Yuchao Li, Jie Chen, Yonghong Tian, Rongrong Ji

This practically limits the application of model compression when the model needs to be deployed on a wide range of devices.

AutoML Model Compression +1

Towards Robustness Against Natural Language Word Substitutions

1 code implementation ICLR 2021 Xinshuai Dong, Anh Tuan Luu, Rongrong Ji, Hong Liu

Robustness against word substitutions has a well-defined and widely acceptable form, i. e., using semantically similar words as substitutions, and thus it is considered as a fundamental stepping-stone towards broader robustness in natural language processing.

Natural Language Inference Sentiment Analysis

Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion

1 code implementation14 Jul 2021 Mingbao Lin, Bohong Chen, Fei Chao, Rongrong Ji

Each filter in our DCFF is firstly given an inter-similarity distribution with a temperature parameter as a filter proxy, on top of which, a fresh Kullback-Leibler divergence based dynamic-coded criterion is proposed to evaluate the filter importance.

Image Classification

GuidedMix-Net: Learning to Improve Pseudo Masks Using Labeled Images as Reference

1 code implementation29 Jun 2021 Peng Tu, Yawen Huang, Rongrong Ji, Feng Zheng, Ling Shao

To take advantage of the labeled examples and guide unlabeled data learning, we further propose a mask generation module to generate high-quality pseudo masks for the unlabeled data.

Semi-Supervised Semantic Segmentation

Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification

1 code implementation CVPR 2021 Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji

In this paper, we propose a joint Modality and Pattern Alignment Network (MPANet) to discover cross-modality nuances in different patterns for visible-infrared person Re-ID, which introduces a modality alleviation module and a pattern alignment module to jointly extract discriminative features.

Person Re-Identification

RSTNet: Captioning With Adaptive Attention on Visual and Non-Visual Words

1 code implementation CVPR 2021 Xuying Zhang, Xiaoshuai Sun, Yunpeng Luo, Jiayi Ji, Yiyi Zhou, Yongjian Wu, Feiyue Huang, Rongrong Ji

Then, we build a BERTbased language model to extract language context and propose Adaptive-Attention (AA) module on top of a transformer decoder to adaptively measure the contribution of visual and language cues before making decisions for word prediction.

Image Captioning Language Modelling +2

HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping

1 code implementation18 Jun 2021 YuHan Wang, Xu Chen, Junwei Zhu, Wenqing Chu, Ying Tai, Chengjie Wang, Jilin Li, Yongjian Wu, Feiyue Huang, Rongrong Ji

In this work, we propose a high fidelity face swapping method, called HifiFace, which can well preserve the face shape of the source face and generate photo-realistic results.

3D Face Reconstruction Face Recognition +2

You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient

1 code implementation4 Jun 2021 Shaokun Zhang, Xiawu Zheng, Chenyi Yang, Yuchao Li, Yan Wang, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji

Motivated by the necessity of efficient inference across various constraints on BERT, we propose a novel approach, YOCO-BERT, to achieve compress once and deploy everywhere.

AutoML Model Compression

1xN Pattern for Pruning Convolutional Neural Networks

1 code implementation31 May 2021 Mingbao Lin, Yuxin Zhang, Yuchao Li, Bohong Chen, Fei Chao, Mengdi Wang, Shen Li, Yonghong Tian, Rongrong Ji

We also provide a workflow of filter rearrangement that first rearranges the weight matrix in the output channel dimension to derive more influential blocks for accuracy improvements and then applies similar rearrangement to the next-layer weights in the input channel dimension to ensure correct convolutional operations.

Network Pruning

Local Relation Learning for Face Forgery Detection

no code implementations6 May 2021 Shen Chen, Taiping Yao, Yang Chen, Shouhong Ding, Jilin Li, Rongrong Ji

Specifically, we propose a Multi-scale Patch Similarity Module (MPSM), which measures the similarity between features of local regions and forms a robust and generalized similarity pattern.

ISTR: End-to-End Instance Segmentation with Transformers

1 code implementation3 May 2021 Jie Hu, Liujuan Cao, Yao Lu, Shengchuan Zhang, Yan Wang, Ke Li, Feiyue Huang, Ling Shao, Rongrong Ji

However, such an upgrade is not applicable to instance segmentation, due to its significantly higher output dimensions compared to object detection.

Instance Segmentation object-detection +3

Carrying out CNN Channel Pruning in a White Box

1 code implementation24 Apr 2021 Yuxin Zhang, Mingbao Lin, Chia-Wen Lin, Jie Chen, Feiyue Huang, Yongjian Wu, Yonghong Tian, Rongrong Ji

Specifically, to model the contribution of each channel to differentiating categories, we develop a class-wise mask for each channel, implemented in a dynamic training manner w. r. t.

Image Classification

Lottery Jackpots Exist in Pre-trained Models

2 code implementations18 Apr 2021 Yuxin Zhang, Mingbao Lin, Yunshan Zhong, Fei Chao, Rongrong Ji

Existing studies achieve the sparsity of neural networks via time-consuming weight training or complex searching on networks with expanded width, which greatly limits the applications of network pruning.

Network Pruning

Learnable Expansion-and-Compression Network for Few-shot Class-Incremental Learning

no code implementations6 Apr 2021 Boyu Yang, Mingbao Lin, Binghao Liu, Mengying Fu, Chang Liu, Rongrong Ji, Qixiang Ye

By tentatively expanding network nodes, LEC-Net enlarges the representation capacity of features, alleviating feature drift of old network from the perspective of model regularization.

Few-Shot Class-Incremental Learning Incremental Learning

Distilling a Powerful Student Model via Online Knowledge Distillation

1 code implementation26 Mar 2021 Shaojie Li, Mingbao Lin, Yan Wang, Yongjian Wu, Yonghong Tian, Ling Shao, Rongrong Ji

Besides, a self-distillation module is adopted to convert the feature map of deeper layers into a shallower one.

Knowledge Distillation

On Evolving Attention Towards Domain Adaptation

no code implementations25 Mar 2021 Kekai Sheng, Ke Li, Xiawu Zheng, Jian Liang, WeiMing Dong, Feiyue Huang, Rongrong Ji, Xing Sun

However, considering that the configuration of attention, i. e., the type and the position of attention module, affects the performance significantly, it is more generalized to optimize the attention configuration automatically to be specialized for arbitrary UDA scenario.

Partial Domain Adaptation Unsupervised Domain Adaptation

Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection

2 code implementations CVPR 2021 Bohao Li, Boyu Yang, Chang Liu, Feng Liu, Rongrong Ji, Qixiang Ye

Few-shot object detection has made substantial progressby representing novel class objects using the feature representation learned upon a set of base class objects.

Few-Shot Object Detection object-detection

Image-to-image Translation via Hierarchical Style Disentanglement

1 code implementation CVPR 2021 Xinyang Li, Shengchuan Zhang, Jie Hu, Liujuan Cao, Xiaopeng Hong, Xudong Mao, Feiyue Huang, Yongjian Wu, Rongrong Ji

Recently, image-to-image translation has made significant progress in achieving both multi-label (\ie, translation conditioned on different labels) and multi-style (\ie, generation with diverse styles) tasks.

Disentanglement Multimodal Unsupervised Image-To-Image Translation +1

SiMaN: Sign-to-Magnitude Network Binarization

2 code implementations16 Feb 2021 Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Fei Chao, Chia-Wen Lin, Ling Shao

In this paper, we show that our weight binarization provides an analytical solution by encoding high-magnitude weights into +1s, and 0s otherwise.


Network Pruning using Adaptive Exemplar Filters

1 code implementation20 Jan 2021 Mingbao Lin, Rongrong Ji, Shaojie Li, Yan Wang, Yongjian Wu, Feiyue Huang, Qixiang Ye

Inspired by the face recognition community, we use a message passing algorithm Affinity Propagation on the weight matrices to obtain an adaptive number of exemplars, which then act as the preserved filters.

Face Recognition Network Pruning

Dual-Level Collaborative Transformer for Image Captioning

1 code implementation16 Jan 2021 Yunpeng Luo, Jiayi Ji, Xiaoshuai Sun, Liujuan Cao, Yongjian Wu, Feiyue Huang, Chia-Wen Lin, Rongrong Ji

Descriptive region features extracted by object detection networks have played an important role in the recent advancements of image captioning.

Descriptive Image Captioning +2

Aha! Adaptive History-Driven Attack for Decision-Based Black-Box Models

1 code implementation ICCV 2021 Jie Li, Rongrong Ji, Peixian Chen, Baochang Zhang, Xiaopeng Hong, Ruixin Zhang, Shaoxin Li, Jilin Li, Feiyue Huang, Yongjian Wu

A common practice is to start from a large perturbation and then iteratively reduce it with a deterministic direction and a random one while keeping it adversarial.

Dimensionality Reduction

TRAR: Routing the Attention Spans in Transformer for Visual Question Answering

1 code implementation ICCV 2021 Yiyi Zhou, Tianhe Ren, Chaoyang Zhu, Xiaoshuai Sun, Jianzhuang Liu, Xinghao Ding, Mingliang Xu, Rongrong Ji

Due to the superior ability of global dependency modeling, Transformer and its variants have become the primary choice of many vision-and-language tasks.

Question Answering Referring Expression +2

EC-DARTS: Inducing Equalized and Consistent Optimization Into DARTS

no code implementations ICCV 2021 Qinqin Zhou, Xiawu Zheng, Liujuan Cao, Bineng Zhong, Teng Xi, Gang Zhang, Errui Ding, Mingliang Xu, Rongrong Ji

EC-DARTS decouples different operations based on their categories to optimize the operation weights so that the operation gap between them is shrinked.

Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network

1 code implementation13 Dec 2020 Jiayi Ji, Yunpeng Luo, Xiaoshuai Sun, Fuhai Chen, Gen Luo, Yongjian Wu, Yue Gao, Rongrong Ji

The latter contains a Global Adaptive Controller that can adaptively fuse the global information into the decoder to guide the caption generation.

Image Captioning

UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object Detection

1 code implementation NeurIPS 2020 Yunhang Shen, Rongrong Ji, Zhiwei Chen, Yongjian Wu, Feiyue Huang

In this paper, we propose a unified WSOD framework, termed UWSOD, to develop a high-capacity general detection model with only image-level labels, which is self-contained and does not require external modules or additional supervision.

object-detection Object Proposal Generation +1

Fast Class-wise Updating for Online Hashing

no code implementations1 Dec 2020 Mingbao Lin, Rongrong Ji, Xiaoshuai Sun, Baochang Zhang, Feiyue Huang, Yonghong Tian, DaCheng Tao

To achieve fast online adaptivity, a class-wise updating method is developed to decompose the binary code learning and alternatively renew the hash functions in a class-wise fashion, which well addresses the burden on large amounts of training batches.

Learning Efficient GANs for Image Translation via Differentiable Masks and co-Attention Distillation

1 code implementation17 Nov 2020 Shaojie Li, Mingbao Lin, Yan Wang, Fei Chao, Ling Shao, Rongrong Ji

The latter simultaneously distills informative attention maps from both the generator and discriminator of a pre-trained model to the searched generator, effectively stabilizing the adversarial training of our light-weight model.


PAMS: Quantized Super-Resolution via Parameterized Max Scale

1 code implementation ECCV 2020 Huixia Li, Chenqian Yan, Shaohui Lin, Xiawu Zheng, Yuchao Li, Baochang Zhang, Fan Yang, Rongrong Ji

Specifically, most state-of-the-art SR models without batch normalization have a large dynamic quantization range, which also serves as another cause of performance drop.

Quantization Super-Resolution +1

Rotated Binary Neural Network

2 code implementations NeurIPS 2020 Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Yan Wang, Yongjian Wu, Feiyue Huang, Chia-Wen Lin

In this paper, for the first time, we explore the influence of angular bias on the quantization error and then introduce a Rotated Binary Neural Network (RBNN), which considers the angle alignment between the full-precision weight vector and its binarized version.

Binarization Quantization

Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning

2 code implementations CVPR 2021 Jinpeng Wang, Yuting Gao, Ke Li, Yiqi Lin, Andy J. Ma, Hao Cheng, Pai Peng, Feiyue Huang, Rongrong Ji, Xing Sun

Then we force the model to pull the feature of the distracting video and the feature of the original video closer, so that the model is explicitly restricted to resist the background influence, focusing more on the motion changes.

Representation Learning Self-Supervised Learning

Binarized Neural Architecture Search for Efficient Object Recognition

no code implementations8 Sep 2020 Hanlin Chen, Li'an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, Rongrong Ji, David Doermann, Guodong Guo

In this paper, binarized neural architecture search (BNAS), with a search space of binarized convolutions, is introduced to produce extremely compressed models to reduce huge computational cost on embedded devices for edge computing.

Edge-computing Face Recognition +2

Dual Channel Hypergraph Collaborative Filtering

no code implementations SIGKDD 2020 Shuyi Ji, Yifan Feng, Rongrong Ji, Xibin Zhao, Wanwan Tang, Yue Gao.

Second, the hypergraph structure is employed for modeling users and items with explicit hybrid high-order correlations.

Collaborative Filtering Recommendation Systems

Anti-Bandit Neural Architecture Search for Model Defense

1 code implementation ECCV 2020 Hanlin Chen, Baochang Zhang, Song Xue, Xuan Gong, Hong Liu, Rongrong Ji, David Doermann

Deep convolutional neural networks (DCNNs) have dominated as the best performers in machine learning, but can be challenged by adversarial attacks.

Denoising Neural Architecture Search

Dual Distribution Alignment Network for Generalizable Person Re-Identification

1 code implementation27 Jul 2020 Peixian Chen, Pingyang Dai, Jianzhuang Liu, Feng Zheng, Qi Tian, Rongrong Ji

Domain generalization (DG) serves as a promising solution to handle person Re-Identification (Re-ID), which trains the model using labels from the source domain alone, and then directly adopts the trained model to the target domain without model updating.

Domain Generalization Generalizable Person Re-identification

Multiple Expert Brainstorming for Domain Adaptive Person Re-identification

2 code implementations ECCV 2020 Yunpeng Zhai, Qixiang Ye, Shijian Lu, Mengxi Jia, Rongrong Ji, Yonghong Tian

Often the best performing deep neural models are ensembles of multiple base-level networks, nevertheless, ensemble learning with respect to domain adaptive person re-ID remains unexplored.

Domain Adaptive Person Re-Identification Ensemble Learning +1

Cogradient Descent for Bilinear Optimization

no code implementations CVPR 2020 Li'an Zhuo, Baochang Zhang, Linlin Yang, Hanlin Chen, Qixiang Ye, David Doermann, Guodong Guo, Rongrong Ji

Conventional learning methods simplify the bilinear model by regarding two intrinsically coupled factors independently, which degrades the optimization procedure.

Image Reconstruction Network Pruning

Rethinking Performance Estimation in Neural Architecture Search

1 code implementation CVPR 2020 Xiawu Zheng, Rongrong Ji, Qiang Wang, Qixiang Ye, Zhenguo Li, Yonghong Tian, Qi Tian

In this paper, we provide a novel yet systematic rethinking of PE in a resource constrained regime, termed budgeted PE (BPE), which precisely and effectively estimates the performance of an architecture sampled from an architecture space.

Neural Architecture Search

Projection & Probability-Driven Black-Box Attack

1 code implementation CVPR 2020 Jie Li, Rongrong Ji, Hong Liu, Jianzhuang Liu, Bineng Zhong, Cheng Deng, Qi Tian

For reducing the solution space, we first model the adversarial perturbation optimization problem as a process of recovering frequency-sparse perturbations with compressed sensing, under the setting that random noise in the low-frequency space is more likely to be adversarial.

Filter Grafting for Deep Neural Networks: Reason, Method, and Cultivation

1 code implementation26 Apr 2020 Hao Cheng, Fanxu Meng, Ke Li, Yuting Gao, Guangming Lu, Xing Sun, Rongrong Ji

To gain a universal improvement on both valid and invalid filters, we compensate grafting with distillation (\textbf{Cultivation}) to overcome the drawback of grafting .