Search Results for author: Jing Shao

Found 57 papers, 28 papers with code

Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception

1 code implementation19 Jan 2023 Bin Huang, Yangguang Li, Enze Xie, Feng Liang, Luya Wang, Mingzhu Shen, Fenggang Liu, Tianqi Wang, Ping Luo, Jing Shao

Recently, the pure camera-based Bird's-Eye-View (BEV) perception removes expensive Lidar sensors, making it a feasible solution for economical autonomous driving.

Autonomous Driving Data Augmentation

BEVBert: Topo-Metric Map Pre-training for Language-guided Navigation

no code implementations8 Dec 2022 Dong An, Yuankai Qi, Yangguang Li, Yan Huang, Liang Wang, Tieniu Tan, Jing Shao

Inspired by the robotics community, we introduce hybrid topo-metric maps into VLN, where a topological map is used for long-term planning and a metric map for short-term reasoning.

Vision and Language Navigation

R$^2$F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference

1 code implementation22 Oct 2022 Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao

Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents.

Natural Language Inference Retrieval

Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies

1 code implementation3 Sep 2022 Xingrun Xing, Yangguang Li, Wei Li, Wenrui Ding, Yalong Jiang, Yufeng Wang, Jing Shao, Chunlei Liu, Xianglong Liu

Second, to improve the robustness of binary models with contextual dependencies, we compute the contextual dynamic embeddings to determine the binarization thresholds in general binary convolutional blocks.

Binarization Inductive Bias

Task-Balanced Distillation for Object Detection

no code implementations5 Aug 2022 Ruining Tang, Zhenyu Liu, Yangguang Li, Yiguo Song, Hui Liu, Qide Wang, Jing Shao, Guifang Duan, Jianrong Tan

To alleviate this problem, a novel Task-decoupled Feature Distillation (TFD) is proposed by flexibly balancing the contributions of classification and regression tasks.

Classification Knowledge Distillation +3

Benchmarking Omni-Vision Representation through the Lens of Visual Realms

1 code implementation14 Jul 2022 Yuanhan Zhang, Zhenfei Yin, Jing Shao, Ziwei Liu

We benchmark ReCo and other advances in omni-vision representation studies that are different in architectures (from CNNs to transformers) and in learning paradigms (from supervised learning to self-supervised learning) on OmniBenchmark.

Contrastive Learning Representation Learning +1

1st Place Solutions for RxR-Habitat Vision-and-Language Navigation Competition (CVPR 2022)

no code implementations23 Jun 2022 Dong An, Zun Wang, Yangguang Li, Yi Wang, Yicong Hong, Yan Huang, Liang Wang, Jing Shao

Our model consists of three modules: the candidate waypoints predictor (CWP), the history enhanced planner and the tryout controller.

Data Augmentation Vision and Language Navigation

Robust Face Anti-Spoofing with Dual Probabilistic Modeling

no code implementations27 Apr 2022 Yuanhan Zhang, Yichao Wu, Zhenfei Yin, Jing Shao, Ziwei Liu

In this work, we attempt to fill this gap by automatically addressing the noise problem from both label and data perspectives in a probabilistic manner.

Face Anti-Spoofing

ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification

no code implementations COLING 2022 Meiqi Chen, Yixin Cao, Kunquan Deng, Mukai Li, Kun Wang, Jing Shao, Yan Zhang

In this paper, we propose a novel Event Relational Graph TransfOrmer (ERGO) framework for DECI, which improves existing state-of-the-art (SOTA) methods upon two aspects.

Event Causality Identification Node Classification +1

Few-shot Forgery Detection via Guided Adversarial Interpolation

no code implementations12 Apr 2022 Haonan Qiu, Siyu Chen, Bei Gan, Kun Wang, Huafeng Shi, Jing Shao, Ziwei Liu

Realistic visual media synthesis is becoming a critical societal issue with the surge of face manipulation models; new forgery approaches emerge at an unprecedented pace.

X-Learner: Learning Cross Sources and Tasks for Universal Visual Representation

no code implementations16 Mar 2022 Yinan He, Gengshi Huang, Siyu Chen, Jianing Teng, Wang Kun, Zhenfei Yin, Lu Sheng, Ziwei Liu, Yu Qiao, Jing Shao

2) Squeeze Stage: X-Learner condenses the model to a reasonable size and learns the universal and generalizable representation for various tasks transferring.

object-detection Object Detection +2

Democratizing Contrastive Language-Image Pre-training: A CLIP Benchmark of Data, Model, and Supervision

1 code implementation11 Mar 2022 Yufeng Cui, Lichen Zhao, Feng Liang, Yangguang Li, Jing Shao

This is because researchers do not choose consistent training recipes and even use different data, hampering the fair comparison between different methods.

RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-training

no code implementations18 Jan 2022 Luya Wang, Feng Liang, Yangguang Li, Honggang Zhang, Wanli Ouyang, Jing Shao

Recently, self-supervised vision transformers have attracted unprecedented attention for their impressive representation learning ability.

Contrastive Learning Representation Learning

SNCSE: Contrastive Learning for Unsupervised Sentence Embedding with Soft Negative Samples

1 code implementation16 Jan 2022 Hao Wang, Yangguang Li, Zhen Huang, Yong Dou, Lingpeng Kong, Jing Shao

To alleviate feature suppression, we propose contrastive learning for unsupervised sentence embedding with soft negative samples (SNCSE).

Contrastive Learning Data Augmentation +5

A Simple Long-Tailed Recognition Baseline via Vision-Language Model

1 code implementation29 Nov 2021 Teli Ma, Shijie Geng, Mengmeng Wang, Jing Shao, Jiasen Lu, Hongsheng Li, Peng Gao, Yu Qiao

Recent advances in large-scale contrastive visual-language pretraining shed light on a new pathway for visual recognition.

Ranked #2 on Long-tail Learning on Places-LT (using extra training data)

Contrastive Learning Language Modelling +3

INTERN: A New Learning Paradigm Towards General Vision

no code implementations16 Nov 2021 Jing Shao, Siyu Chen, Yangguang Li, Kun Wang, Zhenfei Yin, Yinan He, Jianing Teng, Qinghong Sun, Mengya Gao, Jihao Liu, Gengshi Huang, Guanglu Song, Yichao Wu, Yuming Huang, Fenggang Liu, Huan Peng, Shuo Qin, Chengyu Wang, Yujie Wang, Conghui He, Ding Liang, Yu Liu, Fengwei Yu, Junjie Yan, Dahua Lin, Xiaogang Wang, Yu Qiao

Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society.

Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

2 code implementations ICLR 2022 Yangguang Li, Feng Liang, Lichen Zhao, Yufeng Cui, Wanli Ouyang, Jing Shao, Fengwei Yu, Junjie Yan

Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferability to downstream tasks.

Zero-Shot Learning

Few-Shot Domain Expansion for Face Anti-Spoofing

no code implementations27 Jun 2021 Bowen Yang, Jing Zhang, Zhenfei Yin, Jing Shao

In practice, given a handful of labeled samples from a new deployment scenario (target domain) and abundant labeled face images in the existing source domain, the FAS system is expected to perform well in the new scenario without sacrificing the performance on the original domain.

Face Anti-Spoofing Face Recognition +1

ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis

1 code implementation CVPR 2021 Yinan He, Bei Gan, Siyu Chen, Yichun Zhou, Guojun Yin, Luchuan Song, Lu Sheng, Jing Shao, Ziwei Liu

To counter this emerging threat, we construct the ForgeryNet dataset, an extremely large face forgery dataset with unified annotations in image- and video-level data across four tasks: 1) Image Forgery Classification, including two-way (real / fake), three-way (real / fake with identity-replaced forgery approaches / fake with identity-remained forgery approaches), and n-way (real and 15 respective forgery approaches) classification.

Classification General Classification +1

PV-NAS: Practical Neural Architecture Search for Video Recognition

no code implementations2 Nov 2020 ZiHao Wang, Chen Lin, Lu Sheng, Junjie Yan, Jing Shao

Recently, deep learning has been utilized to solve video recognition problem due to its prominent representation ability.

Neural Architecture Search Video Recognition

Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues

2 code implementations ECCV 2020 Yuyang Qian, Guojun Yin, Lu Sheng, Zixuan Chen, Jing Shao

As realistic facial manipulation technologies have achieved remarkable progress, social concerns about potential malicious abuse of these technologies bring out an emerging research topic of face forgery detection.

1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

1 code implementation16 Jun 2020 Siyu Chen, Junting Pan, Guanglu Song, Manyuan Zhang, Hao Shao, Ziyi Lin, Jing Shao, Hongsheng Li, Yu Liu

This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020.

Spatio-Temporal Action Localization Temporal Action Localization

Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization

3 code implementations CVPR 2021 Junting Pan, Siyu Chen, Mike Zheng Shou, Yu Liu, Jing Shao, Hongsheng Li

We propose to explicitly model the Actor-Context-Actor Relation, which is the relation between two actors based on their interactions with the context.

Action Detection Action Recognition +2

Morphing and Sampling Network for Dense Point Cloud Completion

2 code implementations30 Nov 2019 Minghua Liu, Lu Sheng, Sheng Yang, Jing Shao, Shi-Min Hu

3D point cloud completion, the task of inferring the complete geometric shape from a partial point cloud, has been attracting attention in the community.

Point Cloud Completion

Diving into Optimization of Topology in Neural Networks

no code implementations25 Sep 2019 Kun Yuan, Quanquan Li, Yucong Zhou, Jing Shao, Junjie Yan

Seeking effective networks has become one of the most crucial and practical areas in deep learning.

Face Recognition Image Classification +2

Context and Attribute Grounded Dense Captioning

no code implementations CVPR 2019 Guojun Yin, Lu Sheng, Bin Liu, Nenghai Yu, Xiaogang Wang, Jing Shao

Dense captioning aims at simultaneously localizing semantic regions and describing these regions-of-interest (ROIs) with short phrases or sentences in natural language.

Dense Captioning

Video Generation from Single Semantic Label Map

2 code implementations CVPR 2019 Junting Pan, Chengyu Wang, Xu Jia, Jing Shao, Lu Sheng, Junjie Yan, Xiaogang Wang

This paper proposes the novel task of video generation conditioned on a SINGLE semantic label map, which provides a good balance between flexibility and quality in the generation process.

Image Generation Optical Flow Estimation +1

Unsupervised Bi-directional Flow-based Video Generation from one Snapshot

no code implementations3 Mar 2019 Lu Sheng, Junting Pan, Jiaming Guo, Jing Shao, Xiaogang Wang, Chen Change Loy

Imagining multiple consecutive frames given one single snapshot is challenging, since it is difficult to simultaneously predict diverse motions from a single image and faithfully generate novel frames without visual distortions.

Video Generation

Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing

no code implementations CVPR 2019 Xihui Liu, ZiHao Wang, Jing Shao, Xiaogang Wang, Hongsheng Li

Referring expression grounding aims at locating certain objects or persons in an image with a referring expression, where the key challenge is to comprehend and align various types of information from visual and textual domain, such as visual attributes, location and interactions with surrounding regions.

Referring Expression

Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised Detection

1 code implementation16 Sep 2018 Yongcheng Liu, Lu Sheng, Jing Shao, Junjie Yan, Shiming Xiang, Chunhong Pan

Specifically, given the image-level annotations, (1) we first develop a weakly-supervised detection (WSD) model, and then (2) construct an end-to-end multi-label image classification framework augmented by a knowledge distillation module that guides the classification model by the WSD model according to the class-level predictions for the whole image and the object-level visual features for object RoIs.

Classification General Classification +3

Transductive Centroid Projection for Semi-supervised Large-scale Recognition

no code implementations ECCV 2018 Yu Liu, Guanglu Song, Jing Shao, Xiao Jin, Xiaogang Wang

It is inspired by the observation of the weights in classification layer (called extit{anchors}) converge to the central direction of each class in hyperspace.

General Classification

Localization Guided Learning for Pedestrian Attribute Recognition

no code implementations28 Aug 2018 Pengze Liu, Xihui Liu, Junjie Yan, Jing Shao

Pedestrian attribute recognition has attracted many attentions due to its wide applications in scene understanding and person analysis from surveillance videos.

Pedestrian Attribute Recognition Scene Understanding

BlockQNN: Efficient Block-wise Neural Network Architecture Generation

2 code implementations16 Aug 2018 Zhao Zhong, Zichen Yang, Boyang Deng, Junjie Yan, Wei Wu, Jing Shao, Cheng-Lin Liu

The block-wise generation brings unique advantages: (1) it yields state-of-the-art results in comparison to the hand-crafted networks on image classification, particularly, the best network generated by BlockQNN achieves 2. 35% top-1 error rate on CIFAR-10.

Image Classification Q-Learning

Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition

no code implementations ECCV 2018 Guojun Yin, Lu Sheng, Bin Liu, Nenghai Yu, Xiaogang Wang, Jing Shao, Chen Change Loy

We show that by encouraging deep message propagation and interactions between local object features and global predicate features, one can achieve compelling performance in recognizing complex relationships without using any linguistic priors.

Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration

3 code implementations CVPR 2018 Lu Sheng, Ziyi Lin, Jing Shao, Xiaogang Wang

Zero-shot artistic style transfer is an important image synthesis problem aiming at transferring arbitrary style into content images.

Image Generation Image Reconstruction +1

Slicing Convolutional Neural Network for Crowd Video Understanding

no code implementations CVPR 2016 Jing Shao, Chen-Change Loy, Kai Kang, Xiaogang Wang

Learning and capturing both appearance and dynamic representations are pivotal for crowd video understanding.

Video Understanding

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