Search Results for author: Wenhao Jiang

Found 18 papers, 9 papers with code

Learning Grounded Vision-Language Representation for Versatile Understanding in Untrimmed Videos

no code implementations11 Mar 2023 Teng Wang, Jinrui Zhang, Feng Zheng, Wenhao Jiang, Ran Cheng, Ping Luo

TEG learns to adaptively ground the possible event proposals given a set of sentences by estimating the cross-modal distance in a joint semantic space.

Dense Video Captioning Text Generation

VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix

1 code implementation17 Jun 2022 Teng Wang, Wenhao Jiang, Zhichao Lu, Feng Zheng, Ran Cheng, Chengguo Yin, Ping Luo

Existing vision-language pre-training (VLP) methods primarily rely on paired image-text datasets, which are either annotated by enormous human labors, or crawled from the internet followed by elaborate data cleaning techniques.

Contrastive Learning Data Augmentation +1

DynaMixer: A Vision MLP Architecture with Dynamic Mixing

2 code implementations28 Jan 2022 Ziyu Wang, Wenhao Jiang, Yiming Zhu, Li Yuan, Yibing Song, Wei Liu

In contrast with vision transformers and CNNs, the success of MLP-like models shows that simple information fusion operations among tokens and channels can yield a good representation power for deep recognition models.

Image Classification

Poisoning MorphNet for Clean-Label Backdoor Attack to Point Clouds

no code implementations11 May 2021 Guiyu Tian, Wenhao Jiang, Wei Liu, Yadong Mu

To this end, MorphNet jointly optimizes two objectives for sample-adaptive poisoning: a reconstruction loss that preserves the visual similarity between benign / poisoned point clouds, and a classification loss that enforces a modern recognition model of point clouds tends to mis-classify the poisoned sample to a pre-specified target category.

Backdoor Attack Denoising

VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples

1 code implementation CVPR 2021 Tian Pan, Yibing Song, Tianyu Yang, Wenhao Jiang, Wei Liu

By empowering the temporal robustness of the encoder and modeling the temporal decay of the keys, our VideoMoCo improves MoCo temporally based on contrastive learning.

Action Recognition Contrastive Learning +1

Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos

no code implementations ECCV 2020 Shaoxiang Chen, Wenhao Jiang, Wei Liu, Yu-Gang Jiang

Inspired by the fact that there exist cross-modal interactions in the human brain, we propose a novel method for learning pairwise modality interactions in order to better exploit complementary information for each pair of modalities in videos and thus improve performances on both tasks.

Temporally Grounding Language Queries in Videos by Contextual Boundary-aware Prediction

1 code implementation11 Sep 2019 Jingwen Wang, Lin Ma, Wenhao Jiang

The task of temporally grounding language queries in videos is to temporally localize the best matched video segment corresponding to a given language (sentence).

MRI Reconstruction Using Deep Bayesian Estimation

1 code implementation3 Sep 2019 GuanXiong Luo, Na Zhao, Wenhao Jiang, Edward S. Hui, Peng Cao

Purpose: To develop a deep learning-based Bayesian inference for MRI reconstruction.

MRI Reconstruction

Controllable Video Captioning with POS Sequence Guidance Based on Gated Fusion Network

1 code implementation ICCV 2019 Bairui Wang, Lin Ma, Wei zhang, Wenhao Jiang, Jingwen Wang, Wei Liu

In this paper, we propose to guide the video caption generation with Part-of-Speech (POS) information, based on a gated fusion of multiple representations of input videos.

POS Video Captioning

Respiratory Motion Correction in Abdominal MRI using a Densely Connected U-Net with GAN-guided Training

no code implementations24 Jun 2019 Wenhao Jiang, Zhiyu Liu, Kit-Hang Lee, Shihui Chen, Yui-Lun Ng, Qi Dou, Hing-Chiu Chang, Ka-Wai Kwok

Abdominal magnetic resonance imaging (MRI) provides a straightforward way of characterizing tissue and locating lesions of patients as in standard diagnosis.

Hierarchical Photo-Scene Encoder for Album Storytelling

no code implementations2 Feb 2019 Bairui Wang, Lin Ma, Wei zhang, Wenhao Jiang, Feng Zhang

In this paper, we propose a novel model with a hierarchical photo-scene encoder and a reconstructor for the task of album storytelling.

Visual Storytelling

Recurrent Fusion Network for Image Captioning

no code implementations ECCV 2018 Wenhao Jiang, Lin Ma, Yu-Gang Jiang, Wei Liu, Tong Zhang

In this paper, in order to exploit the complementary information from multiple encoders, we propose a novel Recurrent Fusion Network (RFNet) for tackling image captioning.

Image Captioning

Learning to Guide Decoding for Image Captioning

no code implementations3 Apr 2018 Wenhao Jiang, Lin Ma, Xinpeng Chen, Hanwang Zhang, Wei Liu

Recently, much advance has been made in image captioning, and an encoder-decoder framework has achieved outstanding performance for this task.

Image Captioning

Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning

1 code implementation CVPR 2018 Jingwen Wang, Wenhao Jiang, Lin Ma, Wei Liu, Yong Xu

We propose a bidirectional proposal method that effectively exploits both past and future contexts to make proposal predictions.

Dense Video Captioning

Regularizing RNNs for Caption Generation by Reconstructing The Past with The Present

1 code implementation CVPR 2018 Xinpeng Chen, Lin Ma, Wenhao Jiang, Jian Yao, Wei Liu

Recently, caption generation with an encoder-decoder framework has been extensively studied and applied in different domains, such as image captioning, code captioning, and so on.

Image Captioning

Real-Time Neural Style Transfer for Videos

no code implementations CVPR 2017 Hao-Zhi Huang, Hao Wang, Wenhan Luo, Lin Ma, Wenhao Jiang, Xiaolong Zhu, Zhifeng Li, Wei Liu

More specifically, a hybrid loss is proposed to capitalize on the content information of input frames, the style information of a given style image, and the temporal information of consecutive frames.

Style Transfer Video Style Transfer

Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning

no code implementations5 Sep 2015 Wenhao Jiang, Cheng Deng, Wei Liu, Feiping Nie, Fu-Lai Chung, Heng Huang

Domain adaptation problems arise in a variety of applications, where a training dataset from the \textit{source} domain and a test dataset from the \textit{target} domain typically follow different distributions.

Domain Adaptation

Cannot find the paper you are looking for? You can Submit a new open access paper.