283 citations · 1.4k across the 72 of their papers we have counts for
12 papers · 1 filter
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…
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…
Neural Storyboard Artist: Visualizing Stories with Coherent Image Sequences
Shizhe Chen, Bei Liu, Jianlong Fu +6
A storyboard is a sequence of images to illustrate a story containing multiple sentences, which has been a key process to create different story products. In this paper, we tackle…
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…
Learning Rich Image Region Representation for Visual Question Answering
Bei Liu, Zhicheng Huang, Zhaoyang Zeng +2
We propose to boost VQA by leveraging more powerful feature extractors by improving the representation ability of both visual and text features and the ensemble of models. For visu…
360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images
Shih-Han Chou, Cheng Sun, Wen-Yen Chang +3
While there are several widely used object detection datasets, current computer vision algorithms are still limited in conventional images. Such images narrow our vision in a restr…
WSOD^2: Learning Bottom-up and Top-down Objectness Distillation for Weakly-supervised Object Detection
Zhaoyang Zeng, Bei Liu, Jianlong Fu +2
We study on weakly-supervised object detection (WSOD) which plays a vital role in relieving human involvement from object-level annotations. Predominant works integrate region prop…
Learn to Scale: Generating Multipolar Normalized Density Maps for Crowd Counting
Chenfeng Xu, Kai Qiu, Jianlong Fu +3
Dense crowd counting aims to predict thousands of human instances from an image, by calculating integrals of a density map over image pixels. Existing approaches mainly suffer from…
Activitynet 2019 Task 3: Exploring Contexts for Dense Captioning Events in Videos
Shizhe Chen, Yuqing Song, Yida Zhao +5
Contextual reasoning is essential to understand events in long untrimmed videos. In this work, we systematically explore different captioning models with various contexts for the d…
From Words to Sentences: A Progressive Learning Approach for Zero-resource Machine Translation with Visual Pivots
Shizhe Chen, Qin Jin, Jianlong Fu
The neural machine translation model has suffered from the lack of large-scale parallel corpora. In contrast, we humans can learn multi-lingual translations even without parallel t…
Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting
Yanhong Zeng, Jianlong Fu, Hongyang Chao +1
High-quality image inpainting requires filling missing regions in a damaged image with plausible content. Existing works either fill the regions by copying image patches or generat…
Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition
Heliang Zheng, Jianlong Fu, Zheng-Jun Zha +1
Learning subtle yet discriminative features (e.g., beak and eyes for a bird) plays a significant role in fine-grained image recognition. Existing attention-based approaches localiz…