Search Results for author: Junwen Chen

Found 14 papers, 3 papers with code

ATM: Action Temporality Modeling for Video Question Answering

no code implementations5 Sep 2023 Junwen Chen, Jie Zhu, Yu Kong

Despite significant progress in video question answering (VideoQA), existing methods fall short of questions that require causal/temporal reasoning across frames.

Contrastive Learning Optical Flow Estimation +2

Defending Adversarial Patches via Joint Region Localizing and Inpainting

no code implementations26 Jul 2023 Junwen Chen, Xingxing Wei

In this paper, we analyse the properties of adversarial patches, and find that: on the one hand, adversarial patches will lead to the appearance or contextual inconsistency in the target objects; on the other hand, the patch region will show abnormal changes on the high-level feature maps of the objects extracted by a backbone network.

Focusing on what to decode and what to train: Efficient Training with HOI Split Decoders and Specific Target Guided DeNoising

no code implementations5 Jul 2023 Junwen Chen, Yingcheng Wang, Keiji Yanai

However, the current methods redirect the detection target of the object decoder, and the box target is not explicitly separated from the query embeddings, which leads to long and hard training.

Denoising Human-Object Interaction Detection +2

GateHUB: Gated History Unit with Background Suppression for Online Action Detection

no code implementations CVPR 2022 Junwen Chen, Gaurav Mittal, Ye Yu, Yu Kong, Mei Chen

We present GateHUB, Gated History Unit with Background Suppression, that comprises a novel position-guided gated cross-attention mechanism to enhance or suppress parts of the history as per how informative they are for current frame prediction.

Online Action Detection Optical Flow Estimation

Transformer-based Cross-Modal Recipe Embeddings with Large Batch Training

no code implementations10 May 2022 Jing Yang, Junwen Chen, Keiji Yanai

In this paper, we present a cross-modal recipe retrieval framework, Transformer-based Network for Large Batch Training (TNLBT), which is inspired by ACME~(Adversarial Cross-Modal Embedding) and H-T~(Hierarchical Transformer).

Contrastive Learning Image Generation +2

QAHOI: Query-Based Anchors for Human-Object Interaction Detection

1 code implementation16 Dec 2021 Junwen Chen, Keiji Yanai

Human-object interaction (HOI) detection as a downstream of object detection tasks requires localizing pairs of humans and objects and extracting the semantic relationships between humans and objects from an image.

Human-Object Interaction Detection object-detection +1

Explainable Video Entailment With Grounded Visual Evidence

no code implementations ICCV 2021 Junwen Chen, Yu Kong

Video entailment aims at determining if a hypothesis textual statement is entailed or contradicted by a premise video.

Visual Grounding

Group Activity Prediction with Sequential Relational Anticipation Model

1 code implementation ECCV 2020 Junwen Chen, Wentao Bao, Yu Kong

Our model explicitly anticipates both activity features and positions by two graph auto-encoders, aiming to learn a discriminative group representation for group activity prediction.

Activity Prediction

Learning Syntactic and Dynamic Selective Encoding for Document Summarization

no code implementations25 Mar 2020 Haiyang Xu, Yahao He, Kun Han, Junwen Chen, Xiangang Li

Our approach has the following contributions: first, we incorporate syntactic information such as constituency parsing trees into the encoding sequence to learn both the semantic and syntactic information from the document, resulting in more accurate summary; second, we propose a dynamic gate network to select the salient information based on the context of the decoder state, which is essential to document summarization.

Constituency Parsing Document Summarization

Adversarial Multi-Binary Neural Network for Multi-class Classification

no code implementations25 Mar 2020 Haiyang Xu, Junwen Chen, Kun Han, Xiangang Li

Multi-class text classification is one of the key problems in machine learning and natural language processing.

General Classification Multi-class Classification +3

Selective Attention Encoders by Syntactic Graph Convolutional Networks for Document Summarization

no code implementations18 Mar 2020 Haiyang Xu, Yun Wang, Kun Han, Baochang Ma, Junwen Chen, Xiangang Li

Abstractive text summarization is a challenging task, and one need to design a mechanism to effectively extract salient information from the source text and then generate a summary.

Abstractive Text Summarization Document Summarization

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