activity
20152023
most citedSTC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation

619 citations · 2.4k across the 46 of their papers we have counts for

collaborators
Showing 2016Show all

7 papers · 1 filter

cs.CV2016★ 6 cited

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…

cs.CV2016★ 3 cited

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…

cs.CV2016★ 3 cited

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…

cs.CV2016★ 40 cited

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…

cs.CV2016★ 8 cited

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…

cs.CV2016★ 35 cited

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…