216 citations · 1.4k across the 66 of their papers we have counts for
8 papers · 1 filter
Video Scene Parsing with Predictive Feature Learning
Xiaojie Jin, Xin Li, Huaxin Xiao +9
In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we co…
Learning to Detect Multiple Photographic Defects
Ning Yu, Xiaohui Shen, Zhe Lin +2
In this paper, we introduce the problem of simultaneously detecting multiple photographic defects. We aim at detecting the existence, severity, and potential locations of common ph…
High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis
Chao Yang, Xin Lu, Zhe Lin +3
Recent advances in deep learning have shown exciting promise in filling large holes in natural images with semantically plausible and context aware details, impacting fundamental i…
Proposing Plausible Answers for Open-ended Visual Question Answering
Omid Bakhshandeh, Trung Bui, Zhe Lin +1
Answering open-ended questions is an essential capability for any intelligent agent. One of the most interesting recent open-ended question answering challenges is Visual Question…
Top-down Neural Attention by Excitation Backprop
Jianming Zhang, Zhe Lin, Jonathan Brandt +2
We aim to model the top-down attention of a Convolutional Neural Network (CNN) classifier for generating task-specific attention maps. Inspired by a top-down human visual attention…
Photo Aesthetics Ranking Network with Attributes and Content Adaptation
Shu Kong, Xiaohui Shen, Zhe Lin +2
Real-world applications could benefit from the ability to automatically generate a fine-grained ranking of photo aesthetics. However, previous methods for image aesthetics analysis…
Salient Object Subitizing
Jianming Zhang, Shugao Ma, Mehrnoosh Sameki +6
We study the problem of Salient Object Subitizing, i.e. predicting the existence and the number of salient objects in an image using holistic cues. This task is inspired by the abi…
Progressive Attention Networks for Visual Attribute Prediction
Paul Hongsuck Seo, Zhe Lin, Scott Cohen +2
We propose a novel attention model that can accurately attends to target objects of various scales and shapes in images. The model is trained to gradually suppress irrelevant regio…