665 citations · 4.5k across the 236 of their papers we have counts for
41 papers · 1 filter
Neural Simile Recognition with Cyclic Multitask Learning and Local Attention
Jiali Zeng, Linfeng Song, Jinsong Su +3
Simile recognition is to detect simile sentences and to extract simile components, i.e., tenors and vehicles. It involves two subtasks: {\it simile sentence classification} and {\i…
Iterative Dual Domain Adaptation for Neural Machine Translation
Jiali Zeng, Yang Liu, Jinsong Su +4
Previous studies on the domain adaptation for neural machine translation (NMT) mainly focus on the one-pass transferring out-of-domain translation knowledge to in-domain NMT model.…
Graph-based Neural Sentence Ordering
Yongjing Yin, Linfeng Song, Jinsong Su +3
Sentence ordering is to restore the original paragraph from a set of sentences. It involves capturing global dependencies among sentences regardless of their input order. In this p…
Learning Sparse 2D Temporal Adjacent Networks for Temporal Action Localization
Songyang Zhang, Houwen Peng, Le Yang +2
In this report, we introduce the Winner method for HACS Temporal Action Localization Challenge 2019. Temporal action localization is challenging since a target proposal may be rela…
TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning
Zhongjie Yu, Lin Chen, Zhongwei Cheng +1
The successful application of deep learning to many visual recognition tasks relies heavily on the availability of a large amount of labeled data which is usually expensive to obta…
Grounding-Tracking-Integration
Zhengyuan Yang, Tushar Kumar, Tianlang Chen +2
In this paper, we study Tracking by Language that localizes the target box sequence in a video based on a language query. We propose a framework called GTI that decomposes the prob…
Learning 2D Temporal Adjacent Networks for Moment Localization with Natural Language
Songyang Zhang, Houwen Peng, Jianlong Fu +1
We address the problem of retrieving a specific moment from an untrimmed video by a query sentence. This is a challenging problem because a target moment may take place in relation…
Ultrafast Photorealistic Style Transfer via Neural Architecture Search
Jie An, Haoyi Xiong, Jun Huan +1
The key challenge in photorealistic style transfer is that an algorithm should faithfully transfer the style of a reference photo to a content photo while the generated image shoul…
Example-Guided Scene Image Synthesis using Masked Spatial-Channel Attention and Patch-Based Self-Supervision
Haitian Zheng, Haofu Liao, Lele Chen +3
Example-guided image synthesis has been recently attempted to synthesize an image from a semantic label map and an exemplary image. In the task, the additional exemplary image serv…
Open-Ended Visual Question Answering by Multi-Modal Domain Adaptation
Yiming Xu, Lin Chen, Zhongwei Cheng +2
We study the problem of visual question answering (VQA) in images by exploiting supervised domain adaptation, where there is a large amount of labeled data in the source domain but…
Learning Deep Bilinear Transformation for Fine-grained Image Representation
Heliang Zheng, Jianlong Fu, Zheng-Jun Zha +1
Bilinear feature transformation has shown the state-of-the-art performance in learning fine-grained image representations. However, the computational cost to learn pairwise interac…
EnAET: A Self-Trained framework for Semi-Supervised and Supervised Learning with Ensemble Transformations
Xiao Wang, Daisuke Kihara, Jiebo Luo +1
Deep neural networks have been successfully applied to many real-world applications. However, such successes rely heavily on large amounts of labeled data that is expensive to obta…
Defensive Few-shot Learning
Wenbin Li, Lei Wang, Xingxing Zhang +4
This paper investigates a new challenging problem called defensive few-shot learning in order to learn a robust few-shot model against adversarial attacks. Simply applying the exis…
Large-scale Tag-based Font Retrieval with Generative Feature Learning
Tianlang Chen, Zhaowen Wang, Ning Xu +2
Font selection is one of the most important steps in a design workflow. Traditional methods rely on ordered lists which require significant domain knowledge and are often difficult…
SMP Challenge: An Overview of Social Media Prediction Challenge 2019
Bo Wu, Wen-Huang Cheng, Peiye Liu +3
"SMP Challenge" aims to discover novel prediction tasks for numerous data on social multimedia and seek excellent research teams. Making predictions via social multimedia data (e.g…
Unsupervised Pose Flow Learning for Pose Guided Synthesis
Haitian Zheng, Lele Chen, Chenliang Xu +1
Pose guided synthesis aims to generate a new image in an arbitrary target pose while preserving the appearance details from the source image. Existing approaches rely on either har…
Gaussian Temporal Awareness Networks for Action Localization
Fuchen Long, Ting Yao, Zhaofan Qiu +3
Temporally localizing actions in a video is a fundamental challenge in video understanding. Most existing approaches have often drawn inspiration from image object detection and ex…
AI for Earth: Rainforest Conservation by Acoustic Surveillance
Yuan Liu, Zhongwei Cheng, Jie Liu +3
Saving rainforests is a key to halting adverse climate changes. In this paper, we introduce an innovative solution built on acoustic surveillance and machine learning technologies…
A Fast and Accurate One-Stage Approach to Visual Grounding
Zhengyuan Yang, Boqing Gong, Liwei Wang +3
We propose a simple, fast, and accurate one-stage approach to visual grounding, inspired by the following insight. The performances of existing propose-and-rank two-stage methods a…
Exploiting Temporal Relationships in Video Moment Localization with Natural Language
Songyang Zhang, Jinsong Su, Jiebo Luo
We address the problem of video moment localization with natural language, i.e. localizing a video segment described by a natural language sentence. While most prior work focuses o…
Semi-Supervised Adversarial Monocular Depth Estimation
Rongrong Ji, Ke Li, Yan Wang +6
In this paper, we address the problem of monocular depth estimation when only a limited number of training image-depth pairs are available. To achieve a high regression accuracy, t…
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Haofu Liao, Wei-An Lin, S. Kevin Zhou +1
Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training…
Automatic Radiology Report Generation based on Multi-view Image Fusion and Medical Concept Enrichment
Jianbo Yuan, Haofu Liao, Rui Luo +1
Generating radiology reports is time-consuming and requires extensive expertise in practice. Therefore, reliable automatic radiology report generation is highly desired to alleviat…
Fast Universal Style Transfer for Artistic and Photorealistic Rendering
Jie An, Haoyi Xiong, Jiebo Luo +2
Universal style transfer is an image editing task that renders an input content image using the visual style of arbitrary reference images, including both artistic and photorealist…