Search Results for author: Jie zhou

Found 294 papers, 147 papers with code

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

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

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

Metric Learning Person Re-Identification +1

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

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

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

Frame Video-Based Person Re-Identification

BMInf: An Efficient Toolkit for Big Model Inference and Tuning

1 code implementation ACL 2022 Xu Han, Guoyang Zeng, Weilin Zhao, Zhiyuan Liu, Zhengyan Zhang, Jie zhou, Jun Zhang, Jia Chao, Maosong Sun

In recent years, large-scale pre-trained language models (PLMs) containing billions of parameters have achieved promising results on various NLP tasks.

Quantization

Unsupervised Dependency Graph Network

1 code implementation ACL 2022 Yikang Shen, Shawn Tan, Alessandro Sordoni, Peng Li, Jie zhou, Aaron Courville

We introduce a new model, the Unsupervised Dependency Graph Network (UDGN), that can induce dependency structures from raw corpora and the masked language modeling task.

Language Modelling Masked Language Modeling +2

Divide and Denoise: Learning from Noisy Labels in Fine-Grained Entity Typing with Cluster-Wise Loss Correction

no code implementations ACL 2022 Kunyuan Pang, Haoyu Zhang, Jie zhou, Ting Wang

In this work, we propose a clustering-based loss correction framework named Feature Cluster Loss Correction (FCLC), to address these two problems.

Entity Typing

Do Pre-trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation and a Reasonable Approach

no code implementations Findings (ACL) 2022 Xin Lv, Yankai Lin, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Peng Li, Jie zhou

In recent years, pre-trained language models (PLMs) have been shown to capture factual knowledge from massive texts, which encourages the proposal of PLM-based knowledge graph completion (KGC) models.

Knowledge Graph Completion Link Prediction

Selecting Stickers in Open-Domain Dialogue through Multitask Learning

1 code implementation Findings (ACL) 2022 Zhexin Zhang, Yeshuang Zhu, Zhengcong Fei, Jinchao Zhang, Jie zhou

With the increasing popularity of online chatting, stickers are becoming important in our online communication.

Spatial Geometric Reasoning for Room Layout Estimation via Deep Reinforcement Learning

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

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

reinforcement-learning Robot Navigation +1

Rotation-robust Intersection over Union for 3D Object Detection

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

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

2D object detection 3D Object Detection

Deep Hashing with Active Pairwise Supervision

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

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

CodRED: A Cross-Document Relation Extraction Dataset for Acquiring Knowledge in the Wild

1 code implementation EMNLP 2021 Yuan YAO, Jiaju Du, Yankai Lin, Peng Li, Zhiyuan Liu, Jie zhou, Maosong Sun

Existing relation extraction (RE) methods typically focus on extracting relational facts between entity pairs within single sentences or documents.

Relation Extraction

Constructing Emotional Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation

no code implementations Findings (EMNLP) 2021 Lei Shen, Jinchao Zhang, Jiao Ou, Xiaofang Zhao, Jie zhou

To address the above issues, we propose a dual-generative model, Dual-Emp, to simultaneously construct the emotional consensus and utilize some external unpaired data.

Dialogue Generation

欺骗类动词的句法语义研究(On the Syntax and Semantics of Verbs of Cheating)

no code implementations CCL 2021 Shan Wang, Jie zhou

“欺骗是一种常见的社会现象, 但对欺骗类动词的研究十分有限。本文筛选“欺骗”类动词的单句并对其进行大规模的句法依存和语义依存分析。研究显示,“欺骗”类动词在句中作为从属词时, 可作为不同的句法成分和语义角色, 同时此类动词在句法功能上表现出高度的相似性。作为支配词的“欺骗”类动词, 承担不同句法功能时, 表现出不同的句法共现模式。语义上, 本文详细描述、解释了该类动词在语义密度、主客体角色、情境角色和事件关系等维度的语义依存特点。“欺骗”类动词的句法语义虽具有多样性, 但主要的句型为主谓宾句式, 而该句式中最常用的语义搭配模式是施事对涉事进行欺骗行为, 并对涉事产生影响。本研究结合依存语法和框架语义学, 融合定量统计和定性分析探究欺骗类动词的句法语义, 深化了对欺骗行为言语线索以及言说动词的研究。”

MovieChats: Chat like Humans in a Closed Domain

no code implementations EMNLP 2020 Hui Su, Xiaoyu Shen, Zhou Xiao, Zheng Zhang, Ernie Chang, Cheng Zhang, Cheng Niu, Jie zhou

In this work, we take a close look at the movie domain and present a large-scale high-quality corpus with fine-grained annotations in hope of pushing the limit of movie-domain chatbots.

Chatbot

Structural Deep Metric Learning for Room Layout Estimation

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

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

Metric Learning Room Layout Estimation

Bridging the Gap between Prior and Posterior Knowledge Selection for Knowledge-Grounded Dialogue Generation

no code implementations EMNLP 2020 Xiuyi Chen, Fandong Meng, Peng Li, Feilong Chen, Shuang Xu, Bo Xu, Jie zhou

Here, we deal with these issues on two aspects: (1) We enhance the prior selection module with the necessary posterior information obtained from the specially designed Posterior Information Prediction Module (PIPM); (2) We propose a Knowledge Distillation Based Training Strategy (KDBTS) to train the decoder with the knowledge selected from the prior distribution, removing the exposure bias of knowledge selection.

Dialogue Generation Knowledge Distillation

BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

1 code implementation19 May 2022 Yunpeng Zhang, Zheng Zhu, Wenzhao Zheng, JunJie Huang, Guan Huang, Jie zhou, Jiwen Lu

Specifically, BEVerse first performs shared feature extraction and lifting to generate 4D BEV representations from multi-timestamp and multi-view images.

3D Object Detection Autonomous Driving +3

Introspective Deep Metric Learning

1 code implementation9 May 2022 Chengkun Wang, Wenzhao Zheng, Zheng Zhu, Jie zhou, Jiwen Lu

This paper proposes an introspective deep metric learning (IDML) framework for uncertainty-aware comparisons of images.

Image Classification Image Retrieval +1

Monocular 3D Fingerprint Reconstruction and Unwarping

no code implementations2 May 2022 Zhe Cui, Jianjiang Feng, Jie zhou

Compared with contact-based fingerprint acquisition techniques, contactless acquisition has the advantages of less skin distortion, larger fingerprint area, and hygienic acquisition.

3D Reconstruction Shape from Texture

CUP: Curriculum Learning based Prompt Tuning for Implicit Event Argument Extraction

1 code implementation1 May 2022 Jiaju Lin, Qin Chen, Jie zhou, Jian Jin, Liang He

Implicit event argument extraction (EAE) aims to identify arguments that could scatter over the document.

Robust Self-Augmentation for Named Entity Recognition with Meta Reweighting

1 code implementation25 Apr 2022 Linzhi Wu, Pengjun Xie, Jie zhou, Meishan Zhang, Chunping Ma, Guangwei Xu, Min Zhang

Prior research has mainly resorted to heuristic rule-based constraints to reduce the noise for specific self-augmentation methods individually.

Named Entity Recognition NER

Learning to Win Lottery Tickets in BERT Transfer via Task-agnostic Mask Training

1 code implementation24 Apr 2022 Yuanxin Liu, Fandong Meng, Zheng Lin, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou

Firstly, we discover that the success of magnitude pruning can be attributed to the preserved pre-training performance, which correlates with the downstream transferability.

Transfer Learning

WebFace260M: A Benchmark for Million-Scale Deep Face Recognition

no code implementations21 Apr 2022 Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Dalong Du, Jiwen Lu, Jie zhou

For a comprehensive evaluation of face matchers, three recognition tasks are performed under standard, masked and unbiased settings, respectively.

Face Recognition

Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip Translation

no code implementations19 Apr 2022 Siyu Lai, Zhen Yang, Fandong Meng, Xue Zhang, Yufeng Chen, Jinan Xu, Jie zhou

Generating adversarial examples for Neural Machine Translation (NMT) with single Round-Trip Translation (RTT) has achieved promising results by releasing the meaning-preserving restriction.

Machine Translation Translation

HyperDet3D: Learning a Scene-conditioned 3D Object Detector

no code implementations12 Apr 2022 Yu Zheng, Yueqi Duan, Jiwen Lu, Jie zhou, Qi Tian

A bathtub in a library, a sink in an office, a bed in a laundry room -- the counter-intuition suggests that scene provides important prior knowledge for 3D object detection, which instructs to eliminate the ambiguous detection of similar objects.

3D Object Detection

SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation

1 code implementation7 Apr 2022 Yi Wei, Linqing Zhao, Wenzhao Zheng, Zheng Zhu, Yongming Rao, Guan Huang, Jiwen Lu, Jie zhou

In this paper, we propose a SurroundDepth method to incorporate the information from multiple surrounding views to predict depth maps across cameras.

Autonomous Driving Monocular Depth Estimation

FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment

1 code implementation7 Apr 2022 Jinglin Xu, Yongming Rao, Xumin Yu, Guangyi Chen, Jie zhou, Jiwen Lu

Most existing action quality assessment methods rely on the deep features of an entire video to predict the score, which is less reliable due to the non-transparent inference process and poor interpretability.

Action Quality Assessment

Attributable Visual Similarity Learning

1 code implementation28 Mar 2022 Borui Zhang, Wenzhao Zheng, Jie zhou, Jiwen Lu

This paper proposes an attributable visual similarity learning (AVSL) framework for a more accurate and explainable similarity measure between images.

Semantic Similarity Semantic Textual Similarity

LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection

1 code implementation28 Mar 2022 Yi Wei, Zibu Wei, Yongming Rao, Jiaxin Li, Jie zhou, Jiwen Lu

In this paper, we propose the LiDAR Distillation to bridge the domain gap induced by different LiDAR beams for 3D object detection.

3D Object Detection

Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos

1 code implementation26 Mar 2022 Muheng Li, Lei Chen, Yueqi Duan, Zhilan Hu, Jianjiang Feng, Jie zhou, Jiwen Lu

The generated text prompts are paired with corresponding video clips, and together co-train the text encoder and the video encoder via a contrastive approach.

Action Segmentation Action Understanding

Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion

1 code implementation25 Mar 2022 Tianpei Gu, Guangyi Chen, Junlong Li, Chunze Lin, Yongming Rao, Jie zhou, Jiwen Lu

Human behavior has the nature of indeterminacy, which requires the pedestrian trajectory prediction system to model the multi-modality of future motion states.

Pedestrian Trajectory Prediction Trajectory Prediction

A Survey on Cross-Lingual Summarization

no code implementations23 Mar 2022 Jiaan Wang, Fandong Meng, Duo Zheng, Yunlong Liang, Zhixu Li, Jianfeng Qu, Jie zhou

Cross-lingual summarization is the task of generating a summary in one language (e. g., English) for the given document(s) in a different language (e. g., Chinese).

Spot the Difference: A Cooperative Object-Referring Game in Non-Perfectly Co-Observable Scene

no code implementations16 Mar 2022 Duo Zheng, Fandong Meng, Qingyi Si, Hairun Fan, Zipeng Xu, Jie zhou, Fangxiang Feng, Xiaojie Wang

Visual dialog has witnessed great progress after introducing various vision-oriented goals into the conversation, especially such as GuessWhich and GuessWhat, where the only image is visible by either and both of the questioner and the answerer, respectively.

Visual Dialog

Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement

2 code implementations10 Mar 2022 Xiuwei Xu, Yifan Wang, Yu Zheng, Yongming Rao, Jie zhou, Jiwen Lu

In this paper, we propose a weakly-supervised approach for 3D object detection, which makes it possible to train a strong 3D detector with position-level annotations (i. e. annotations of object centers).

3D Object Detection Domain Adaptation

A Variational Hierarchical Model for Neural Cross-Lingual Summarization

1 code implementation ACL 2022 Yunlong Liang, Fandong Meng, Chulun Zhou, Jinan Xu, Yufeng Chen, Jinsong Su, Jie zhou

The goal of the cross-lingual summarization (CLS) is to convert a document in one language (e. g., English) to a summary in another one (e. g., Chinese).

Machine Translation Translation

Towards Robust Online Dialogue Response Generation

no code implementations7 Mar 2022 Leyang Cui, Fandong Meng, Yijin Liu, Jie zhou, Yue Zhang

Although pre-trained sequence-to-sequence models have achieved great success in dialogue response generation, chatbots still suffer from generating inconsistent responses in real-world practice, especially in multi-turn settings.

Chatbot Re-Ranking +1

Conditional Bilingual Mutual Information Based Adaptive Training for Neural Machine Translation

1 code implementation ACL 2022 Songming Zhang, Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu, Jian Liu, Jie zhou

Token-level adaptive training approaches can alleviate the token imbalance problem and thus improve neural machine translation, through re-weighting the losses of different target tokens based on specific statistical metrics (e. g., token frequency or mutual information).

Language Modelling Machine Translation +1

TSAM: A Two-Stream Attention Model for Causal Emotion Entailment

1 code implementation2 Mar 2022 Duzhen Zhang, Zhen Yang, Fandong Meng, Xiuyi Chen, Jie zhou

Causal Emotion Entailment (CEE) aims to discover the potential causes behind an emotion in a conversational utterance.

Causal Emotion Entailment

MSCTD: A Multimodal Sentiment Chat Translation Dataset

1 code implementation ACL 2022 Yunlong Liang, Fandong Meng, Jinan Xu, Yufeng Chen, Jie zhou

In this work, we introduce a new task named Multimodal Chat Translation (MCT), aiming to generate more accurate translations with the help of the associated dialogue history and visual context.

Multimodal Machine Translation Sentiment Analysis +1

Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation

no code implementations ACL 2022 Chulun Zhou, Fandong Meng, Jie zhou, Min Zhang, Hongji Wang, Jinsong Su

Most dominant neural machine translation (NMT) models are restricted to make predictions only according to the local context of preceding words in a left-to-right manner.

14 Knowledge Distillation +3

ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization

1 code implementation11 Feb 2022 Jiaan Wang, Fandong Meng, Ziyao Lu, Duo Zheng, Zhixu Li, Jianfeng Qu, Jie zhou

We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents.

Mental Health Assessment for the Chatbots

no code implementations14 Jan 2022 Yong Shan, Jinchao Zhang, Zekang Li, Yang Feng, Jie zhou

Previous researches on dialogue system assessment usually focus on the quality evaluation (e. g. fluency, relevance, etc) of responses generated by the chatbots, which are local and technical metrics.

Chatbot

Coarse-to-Fine Embedded PatchMatch and Multi-Scale Dynamic Aggregation for Reference-based Super-Resolution

1 code implementation12 Jan 2022 Bin Xia, Yapeng Tian, Yucheng Hang, Wenming Yang, Qingmin Liao, Jie zhou

To improve matching efficiency, we design a novel Embedded PatchMacth scheme with random samples propagation, which involves end-to-end training with asymptotic linear computational cost to the input size.

Reference-based Super-Resolution

Efficient Non-Local Contrastive Attention for Image Super-Resolution

1 code implementation11 Jan 2022 Bin Xia, Yucheng Hang, Yapeng Tian, Wenming Yang, Qingmin Liao, Jie zhou

To demonstrate the effectiveness of ENLCA, we build an architecture called Efficient Non-Local Contrastive Network (ENLCN) by adding a few of our modules in a simple backbone.

Contrastive Learning Image Super-Resolution

Robust and Precise Facial Landmark Detection by Self-Calibrated Pose Attention Network

no code implementations23 Dec 2021 Jun Wan, Hui Xi, Jie zhou, Zhihui Lai, Witold Pedrycz, Xu Wang, Hang Sun

We show that by integrating the BALI fields and SCPA model into a novel self-calibrated pose attention network, more facial prior knowledge can be learned and the detection accuracy and robustness of our method for faces with large poses and heavy occlusions have been improved.

Facial Landmark Detection

Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network

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

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

Adversarial Attack Semantic Segmentation

Model Uncertainty-Aware Knowledge Amalgamation for Pre-Trained Language Models

no code implementations14 Dec 2021 Lei LI, Yankai Lin, Xuancheng Ren, Guangxiang Zhao, Peng Li, Jie zhou, Xu sun

As many fine-tuned pre-trained language models~(PLMs) with promising performance are generously released, investigating better ways to reuse these models is vital as it can greatly reduce the retraining computational cost and the potential environmental side-effects.

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

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

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

Instance Segmentation Language Modelling +4

On Transferability of Prompt Tuning for Natural Language Processing

1 code implementation12 Nov 2021 Yusheng Su, Xiaozhi Wang, Yujia Qin, Chi-Min Chan, Yankai Lin, Huadong Wang, Kaiyue Wen, Zhiyuan Liu, Peng Li, Juanzi Li, Lei Hou, Maosong Sun, Jie zhou

To explore whether we can improve PT via prompt transfer, we empirically investigate the transferability of soft prompts across different downstream tasks and PLMs in this work.

Natural Language Understanding Pretrained Language Models +1

Exploring Universal Intrinsic Task Subspace via Prompt Tuning

1 code implementation15 Oct 2021 Yujia Qin, Xiaozhi Wang, Yusheng Su, Yankai Lin, Ning Ding, Jing Yi, Weize Chen, Zhiyuan Liu, Juanzi Li, Lei Hou, Peng Li, Maosong Sun, Jie zhou

In the experiments, we study diverse few-shot NLP tasks and surprisingly find that in a 250-dimensional subspace found with 100 tasks, by only tuning 250 free parameters, we can recover 97% and 83% of the full prompt tuning performance for 100 seen tasks (using different training data) and 20 unseen tasks, respectively, showing great generalization ability of the found intrinsic task subspace.

RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models

1 code implementation EMNLP 2021 Wenkai Yang, Yankai Lin, Peng Li, Jie zhou, Xu sun

Motivated by this observation, we construct a word-based robustness-aware perturbation to distinguish poisoned samples from clean samples to defend against the backdoor attacks on natural language processing (NLP) models.

Sentiment Analysis

WeTS: A Benchmark for Translation Suggestion

1 code implementation11 Oct 2021 Zhen Yang, Fandong Meng, Yingxue Zhang, Ernan Li, Jie zhou

To break this limitation, we create a benchmark data set for TS, called \emph{WeTS}, which contains golden corpus annotated by expert translators on four translation directions.

Machine Translation Translation

Topology-Imbalance Learning for Semi-Supervised Node Classification

1 code implementation NeurIPS 2021 Deli Chen, Yankai Lin, Guangxiang Zhao, Xuancheng Ren, Peng Li, Jie zhou, Xu sun

The class imbalance problem, as an important issue in learning node representations, has drawn increasing attention from the community.

Classification Node Classification

Simulated annealing for optimization of graphs and sequences

no code implementations1 Oct 2021 Xianggen Liu, Pengyong Li, Fandong Meng, Hao Zhou, Huasong Zhong, Jie zhou, Lili Mou, Sen Song

The key idea is to integrate powerful neural networks into metaheuristics (e. g., simulated annealing, SA) to restrict the search space in discrete optimization.

Paraphrase Generation

Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search

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

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

Image Classification Neural Architecture Search

Structure-Preserving Image Super-Resolution

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

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

Image Super-Resolution SSIM

Dynamic Knowledge Distillation for Pre-trained Language Models

1 code implementation EMNLP 2021 Lei LI, Yankai Lin, Shuhuai Ren, Peng Li, Jie zhou, Xu sun

Knowledge distillation~(KD) has been proved effective for compressing large-scale pre-trained language models.

Knowledge Distillation

GoG: Relation-aware Graph-over-Graph Network for Visual Dialog

no code implementations Findings (ACL) 2021 Feilong Chen, Xiuyi Chen, Fandong Meng, Peng Li, Jie zhou

Specifically, GoG consists of three sequential graphs: 1) H-Graph, which aims to capture coreference relations among dialog history; 2) History-aware Q-Graph, which aims to fully understand the question through capturing dependency relations between words based on coreference resolution on the dialog history; and 3) Question-aware I-Graph, which aims to capture the relations between objects in an image based on fully question representation.

Coreference Resolution Visual Dialog

Multimodal Incremental Transformer with Visual Grounding for Visual Dialogue Generation

1 code implementation Findings (ACL) 2021 Feilong Chen, Fandong Meng, Xiuyi Chen, Peng Li, Jie zhou

Visual dialogue is a challenging task since it needs to answer a series of coherent questions on the basis of understanding the visual environment.

Dialogue Generation Visual Grounding

Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation

no code implementations16 Sep 2021 Lei Shen, Jinchao Zhang, Jiao Ou, Xiaofang Zhao, Jie zhou

To address the above issues, we propose a dual-generative model, Dual-Emp, to simultaneously construct the emotion consensus and utilize some external unpaired data.

Dialogue Generation

Structure-Enhanced Pop Music Generation via Harmony-Aware Learning

no code implementations14 Sep 2021 Xueyao Zhang, Jinchao Zhang, Yao Qiu, Li Wang, Jie zhou

Besides, when chords evolve into chord progression, the texture and the form can be bridged by the harmony naturally, which contributes to the joint learning of the two structures.

Music Generation

Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks

no code implementations EMNLP 2021 Yao Qiu, Jinchao Zhang, Jie zhou

Loading models pre-trained on the large-scale corpus in the general domain and fine-tuning them on specific downstream tasks is gradually becoming a paradigm in Natural Language Processing.

Domain Adaptation Language Modelling

Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training

no code implementations14 Sep 2021 Yao Qiu, Jinchao Zhang, Huiying Ren, Jie zhou

In this way, our negative instances are fluent, context-related, and more challenging for the model to learn, while can not be positive.

Chatbot

Competence-based Curriculum Learning for Multilingual Machine Translation

no code implementations Findings (EMNLP) 2021 Mingliang Zhang, Fandong Meng, Yunhai Tong, Jie zhou

Therefore, we focus on balancing the learning competencies of different languages and propose Competence-based Curriculum Learning for Multilingual Machine Translation, named CCL-M.

Machine Translation Translation

Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser

1 code implementation Findings (EMNLP) 2021 Duo Zheng, Zipeng Xu, Fandong Meng, Xiaojie Wang, Jiaan Wang, Jie zhou

To enhance VD Questioner: 1) we propose a Related entity enhanced Questioner (ReeQ) that generates questions under the guidance of related entities and learns entity-based questioning strategy from human dialogs; 2) we propose an Augmented Guesser (AugG) that is strong and is optimized for the VD setting especially.

Visual Dialog

Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark

1 code implementation4 Sep 2021 Zhengcong Fei, Zekang Li, Jinchao Zhang, Yang Feng, Jie zhou

Compared to previous dialogue tasks, MOD is much more challenging since it requires the model to understand the multimodal elements as well as the emotions behind them.

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

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

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

Depth Estimation

Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification

1 code implementation EMNLP 2021 Shuhuai Ren, Jinchao Zhang, Lei LI, Xu sun, Jie zhou

Data augmentation aims to enrich training samples for alleviating the overfitting issue in low-resource or class-imbalanced situations.

Classification Data Augmentation +1

Scheduled Sampling Based on Decoding Steps for Neural Machine Translation

1 code implementation EMNLP 2021 Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou

Its core motivation is to simulate the inference scene during training by replacing ground-truth tokens with predicted tokens, thus bridging the gap between training and inference.

Machine Translation Text Summarization +1

Deep Relational Metric Learning

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

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

Image Clustering Metric Learning

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

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

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

Causal Inference Fine-Grained Image Classification +5

PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

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

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

Point Cloud Completion

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

2 code implementations ICCV 2021 Yongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie zhou

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

2D object detection 3D Object Detection +2

Towards Interpretable Deep Metric Learning with Structural Matching

1 code implementation ICCV 2021 Wenliang Zhao, Yongming Rao, Ziyi Wang, Jiwen Lu, Jie zhou

Our method is model-agnostic, which can be applied to off-the-shelf backbone networks and metric learning methods.

Metric Learning

PatrickStar: Parallel Training of Pre-trained Models via Chunk-based Memory Management

1 code implementation12 Aug 2021 Jiarui Fang, Yang Yu, Zilin Zhu, Shenggui Li, Yang You, Jie zhou

Therefore, we proposed a system called PatrickStar to lower the hardware requirements of PTMs and make them accessible to everyone.

Person Re-identification via Attention Pyramid

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

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

Person Re-Identification

Generalizable Mixed-Precision Quantization via Attribution Rank Preservation

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

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

Quantization

WeChat Neural Machine Translation Systems for WMT21

no code implementations WMT (EMNLP) 2021 Xianfeng Zeng, Yijin Liu, Ernan Li, Qiu Ran, Fandong Meng, Peng Li, Jinan Xu, Jie zhou

This paper introduces WeChat AI's participation in WMT 2021 shared news translation task on English->Chinese, English->Japanese, Japanese->English and English->German.

Knowledge Distillation Machine Translation +3

SimpModeling: Sketching Implicit Field to Guide Mesh Modeling for 3D Animalmorphic Head Design

1 code implementation5 Aug 2021 Zhongjin Luo, Jie zhou, Heming Zhu, Dong Du, Xiaoguang Han, Hongbo Fu

In this work, we propose SimpModeling, a novel sketch-based system for helping users, especially amateur users, easily model 3D animalmorphic heads - a prevalent kind of heads in character design.

Rethinking Stealthiness of Backdoor Attack against NLP Models

1 code implementation ACL 2021 Wenkai Yang, Yankai Lin, Peng Li, Jie zhou, Xu sun

In this work, we point out a potential problem of current backdoor attacking research: its evaluation ignores the stealthiness of backdoor attacks, and most of existing backdoor attacking methods are not stealthy either to system deployers or to system users.

Backdoor Attack Data Augmentation +2

Human Trajectory Prediction via Counterfactual Analysis

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

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

Autonomous Vehicles Trajectory Forecasting

Modeling Bilingual Conversational Characteristics for Neural Chat Translation

1 code implementation ACL 2021 Yunlong Liang, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou

Despite the impressive performance of sentence-level and context-aware Neural Machine Translation (NMT), there still remain challenges to translate bilingual conversational text due to its inherent characteristics such as role preference, dialogue coherence, and translation consistency.

Machine Translation Translation

Confidence-Aware Scheduled Sampling for Neural Machine Translation

1 code implementation Findings (ACL) 2021 Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou

In this way, the model is exactly exposed to predicted tokens for high-confidence positions and still ground-truth tokens for low-confidence positions.

Machine Translation Translation

Target-Oriented Fine-tuning for Zero-Resource Named Entity Recognition

1 code implementation Findings (ACL) 2021 Ying Zhang, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou

In this paper, we tackle the problem by transferring knowledge from three aspects, i. e., domain, language and task, and strengthening connections among them.

Named Entity Recognition NER +1

Modeling Explicit Concerning States for Reinforcement Learning in Visual Dialogue

1 code implementation12 Jul 2021 Zipeng Xu, Fandong Meng, Xiaojie Wang, Duo Zheng, Chenxu Lv, Jie zhou

In Reinforcement Learning, it is crucial to represent states and assign rewards based on the action-caused transitions of states.

reinforcement-learning

Similarity-Aware Fusion Network for 3D Semantic Segmentation

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

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

3D Semantic Segmentation

Global Filter Networks for Image Classification

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

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

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

Classification Domain Generalization +1

Rethinking the Evaluation of Neural Machine Translation

no code implementations29 Jun 2021 Jianhao Yan, Chenming Wu, Fandong Meng, Jie zhou

However, this evaluation framework suffers from high search errors brought by heuristic search algorithms and is limited by its nature of evaluation over one best candidate.

14 Machine Translation +1

Deep Compositional Metric Learning

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

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

Metric Learning

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

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

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

Face Clustering Graph Clustering

Pseudo Facial Generation With Extreme Poses for Face Recognition

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

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

Face Recognition

Self-Supervised Video Hashing via Bidirectional Transformers

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

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

Video Retrieval

Sequence-Level Training for Non-Autoregressive Neural Machine Translation

1 code implementation CL (ACL) 2021 Chenze Shao, Yang Feng, Jinchao Zhang, Fandong Meng, Jie zhou

Non-Autoregressive Neural Machine Translation (NAT) removes the autoregressive mechanism and achieves significant decoding speedup through generating target words independently and simultaneously.

Machine Translation Translation

Evaluating Modules in Graph Contrastive Learning

no code implementations15 Jun 2021 Ganqu Cui, Yufeng Du, Cheng Yang, Jie zhou, Liang Xu, LiFeng Wang, Zhiyuan Liu

The recent emergence of contrastive learning approaches facilitates the research on graph representation learning (GRL), introducing graph contrastive learning (GCL) into the literature.

Contrastive Learning Graph Classification +1

Marginal Utility Diminishes: Exploring the Minimum Knowledge for BERT Knowledge Distillation

1 code implementation ACL 2021 Yuanxin Liu, Fandong Meng, Zheng Lin, Weiping Wang, Jie zhou

In this paper, however, we observe that although distilling the teacher's hidden state knowledge (HSK) is helpful, the performance gain (marginal utility) diminishes quickly as more HSK is distilled.

Knowledge Distillation

GTM: A Generative Triple-Wise Model for Conversational Question Generation

no code implementations ACL 2021 Lei Shen, Fandong Meng, Jinchao Zhang, Yang Feng, Jie zhou

Generating some appealing questions in open-domain conversations is an effective way to improve human-machine interactions and lead the topic to a broader or deeper direction.

Question Generation

Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot Consistency

1 code implementation Findings (ACL) 2021 Zekang Li, Jinchao Zhang, Zhengcong Fei, Yang Feng, Jie zhou

Employing human judges to interact with chatbots on purpose to check their capacities is costly and low-efficient, and difficult to get rid of subjective bias.

Chatbot Natural Language Inference

Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances

1 code implementation ACL 2021 Zekang Li, Jinchao Zhang, Zhengcong Fei, Yang Feng, Jie zhou

Nowadays, open-domain dialogue models can generate acceptable responses according to the historical context based on the large-scale pre-trained language models.

Dialogue Evaluation Dialogue Generation

DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

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

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

Image Classification

Exploring Dynamic Selection of Branch Expansion Orders for Code Generation

1 code implementation ACL 2021 Hui Jiang, Chulun Zhou, Fandong Meng, Biao Zhang, Jie zhou, Degen Huang, Qingqiang Wu, Jinsong Su

Due to the great potential in facilitating software development, code generation has attracted increasing attention recently.

Code Generation

Context Tracking Network: Graph-based Context Modeling for Implicit Discourse Relation Recognition

no code implementations NAACL 2021 Yingxue Zhang, Fandong Meng, Peng Li, Ping Jian, Jie zhou

Implicit discourse relation recognition (IDRR) aims to identify logical relations between two adjacent sentences in the discourse.

Fully Hyperbolic Neural Networks

1 code implementation ACL 2022 Weize Chen, Xu Han, Yankai Lin, Hexu Zhao, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

Hyperbolic neural networks have shown great potential for modeling complex data.

Knowledge Inheritance for Pre-trained Language Models

2 code implementations28 May 2021 Yujia Qin, Yankai Lin, Jing Yi, Jiajie Zhang, Xu Han, Zhengyan Zhang, Yusheng Su, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

Specifically, we introduce a pre-training framework named "knowledge inheritance" (KI) and explore how could knowledge distillation serve as auxiliary supervision during pre-training to efficiently learn larger PLMs.

Domain Adaptation Knowledge Distillation +2

Selective Knowledge Distillation for Neural Machine Translation

1 code implementation ACL 2021 Fusheng Wang, Jianhao Yan, Fandong Meng, Jie zhou

As an active research field in NMT, knowledge distillation is widely applied to enhance the model's performance by transferring teacher model's knowledge on each training sample.

14 Knowledge Distillation +2

Bilingual Mutual Information Based Adaptive Training for Neural Machine Translation

1 code implementation ACL 2021 Yangyifan Xu, Yijin Liu, Fandong Meng, Jiajun Zhang, Jinan Xu, Jie zhou

Recently, token-level adaptive training has achieved promising improvement in machine translation, where the cross-entropy loss function is adjusted by assigning different training weights to different tokens, in order to alleviate the token imbalance problem.

Machine Translation Translation

Prevent the Language Model from being Overconfident in Neural Machine Translation

1 code implementation ACL 2021 Mengqi Miao, Fandong Meng, Yijin Liu, Xiao-Hua Zhou, Jie zhou

The Neural Machine Translation (NMT) model is essentially a joint language model conditioned on both the source sentence and partial translation.

Language Modelling Machine Translation +1

Manual Evaluation Matters: Reviewing Test Protocols of Distantly Supervised Relation Extraction

1 code implementation Findings (ACL) 2021 Tianyu Gao, Xu Han, Keyue Qiu, Yuzhuo Bai, Zhiyu Xie, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

Distantly supervised (DS) relation extraction (RE) has attracted much attention in the past few years as it can utilize large-scale auto-labeled data.

Relation Extraction

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

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

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

3D Object Detection

ER-IQA: Boosting Perceptual Quality Assessment Using External Reference Images

no code implementations6 May 2021 Jingyu Guo, Wei Wang, Wenming Yang, Qingmin Liao, Jie zhou

In this paper, we introduce a brand new scheme, namely external-reference image quality assessment (ER-IQA), by introducing external reference images to bridge the gap between FR and NR-IQA.

Image Quality Assessment

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

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

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

Human Detection Multi-Person Pose Estimation

Meta-Mining Discriminative Samples for Kinship Verification

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

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

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

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

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

Face Clustering Graph Clustering

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

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

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

 Ranked #1 on Face Verification on IJB-C (dataset metric)

Face Recognition Face Verification

Epidemic spreading under pathogen evolution

no code implementations19 Feb 2021 Xiyun Zhang, Zhongyuan Ruan, Muhua Zheng, Jie zhou, Stefano Boccaletti, Baruch Barzel

Specifically, we detect a new pandemic phase - the mutated phase - in which, despite the fact that the pathogen is initially non-pandemic (R0 < 1), it may still spread due to the emergence of a critical mutation.

Separable Structure Modeling for Semi-supervised Video Object Segmentation

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

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

One-shot visual object segmentation Video Semantic Segmentation

CSS-LM: A Contrastive Framework for Semi-supervised Fine-tuning of Pre-trained Language Models

1 code implementation7 Feb 2021 Yusheng Su, Xu Han, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Peng Li, Jie zhou, Maosong Sun

We then perform contrastive semi-supervised learning on both the retrieved unlabeled and original labeled instances to help PLMs capture crucial task-related semantic features.

MAX Phase Zr2SeC and Its Thermal Conduction Behavior

no code implementations4 Feb 2021 Ke Chen, Xiaojing Bai, Xulin Mu, Pengfei Yan, Nianxiang Qiu, Youbing Li, Jie zhou, Yujie Song, Yiming Zhang, Shiyu Du, Zhifang Chai, Qing Huang

The elemental diversity is crucial to screen out ternary MAX phases with outstanding properties via tuning of bonding types and strength between constitutive atoms.

Materials Science

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

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

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

Image Retrieval Semantic Similarity +1

Retro-Reflective Beam Communications with Spatially Separated Laser Resonator

no code implementations30 Jan 2021 Mingliang Xiong, Mingqing Liu, Qingwei Jiang, Jie zhou, Qingwen Liu, Hao Deng

Optical wireless communications (OWC) utilizing infrared or visible light as the carrier attracts great attention in 6G research.

WeChat AI & ICT's Submission for DSTC9 Interactive Dialogue Evaluation Track

no code implementations20 Jan 2021 Zekang Li, Zongjia Li, Jinchao Zhang, Yang Feng, Jie zhou

We participate in the DSTC9 Interactive Dialogue Evaluation Track (Gunasekara et al. 2020) sub-task 1 (Knowledge Grounded Dialogue) and sub-task 2 (Interactive Dialogue).

Dialogue Evaluation Language Modelling

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

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

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

Monocular Depth Estimation Multi-Task Learning +2

Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds

no code implementations7 Jan 2021 Jingyu Gong, Jiachen Xu, Xin Tan, Jie zhou, Yanyun Qu, Yuan Xie, Lizhuang Ma

Boundary information plays a significant role in 2D image segmentation, while usually being ignored in 3D point cloud segmentation where ambiguous features might be generated in feature extraction, leading to misclassification in the transition area between two objects.

Point Cloud Segmentation Semantic Segmentation

Weakly-Supervised Saliency Detection via Salient Object Subitizing

no code implementations4 Jan 2021 Xiaoyang Zheng, Xin Tan, Jie zhou, Lizhuang Ma, Rynson W. H. Lau

This allows the supervision to be aligned with the property of saliency detection, where the salient objects of an image could be from more than one class.

Object Detection Saliency Detection +2

Frequency-Aware Spatiotemporal Transformers for Video Inpainting Detection

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

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

Video Inpainting

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

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

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

Point Cloud Segmentation Scene Segmentation

Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification

no code implementations14 Dec 2020 Deli Chen, Yankai Lin, Lei LI, Xuancheng Ren, Peng Li, Jie zhou, Xu sun

Graph Contrastive Learning (GCL) has proven highly effective in promoting the performance of Semi-Supervised Node Classification (SSNC).

Contrastive Learning Graph Learning +1

Emotional Conversation Generation with Heterogeneous Graph Neural Network

1 code implementation9 Dec 2020 Yunlong Liang, Fandong Meng, Ying Zhang, Jinan Xu, Yufeng Chen, Jie zhou

Firstly, we design a Heterogeneous Graph-Based Encoder to represent the conversation content (i. e., the dialogue history, its emotion flow, facial expressions, audio, and speakers' personalities) with a heterogeneous graph neural network, and then predict suitable emotions for feedback.