283 citations · 1.4k across the 72 of their papers we have counts for
8 papers · 1 filter
Multi-Scale 2D Temporal Adjacent Networks for Moment Localization with Natural Language
Songyang Zhang, Houwen Peng, Jianlong Fu +2
We address the problem of retrieving a specific moment from an untrimmed video by natural language. It is a challenging problem because a target moment may take place in the contex…
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search
Houwen Peng, Hao Du, Hongyuan Yu +3
One-shot weight sharing methods have recently drawn great attention in neural architecture search due to high efficiency and competitive performance. However, weight sharing across…
Revisiting Anchor Mechanisms for Temporal Action Localization
Le Yang, Houwen Peng, Dingwen Zhang +2
Most of the current action localization methods follow an anchor-based pipeline: depicting action instances by pre-defined anchors, learning to select the anchors closest to the gr…
Learning Joint Spatial-Temporal Transformations for Video Inpainting
Yanhong Zeng, Jianlong Fu, Hongyang Chao
High-quality video inpainting that completes missing regions in video frames is a promising yet challenging task. State-of-the-art approaches adopt attention models to complete a f…
Learning Texture Transformer Network for Image Super-Resolution
Fuzhi Yang, Huan Yang, Jianlong Fu +2
We study on image super-resolution (SR), which aims to recover realistic textures from a low-resolution (LR) image. Recent progress has been made by taking high-resolution images a…
Cyclic Differentiable Architecture Search
Hongyuan Yu, Houwen Peng, Yan Huang +4
Differentiable ARchiTecture Search, i.e., DARTS, has drawn great attention in neural architecture search. It tries to find the optimal architecture in a shallow search network and…
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte +60
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input im…
Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers
Zhicheng Huang, Zhaoyang Zeng, Bei Liu +2
We propose Pixel-BERT to align image pixels with text by deep multi-modal transformers that jointly learn visual and language embedding in a unified end-to-end framework. We aim to…