219 citations · 497 across the 12 of their papers we have counts for
13 papers
EgoObjects: A Large-Scale Egocentric Dataset for Fine-Grained Object Understanding
Chenchen Zhu, Fanyi Xiao, Andres Alvarado +6
Object understanding in egocentric visual data is arguably a fundamental research topic in egocentric vision. However, existing object datasets are either non-egocentric or have li…
Exploring Open-Vocabulary Semantic Segmentation without Human Labels
Jun Chen, Deyao Zhu, Guocheng Qian +6
Semantic segmentation is a crucial task in computer vision that involves segmenting images into semantically meaningful regions at the pixel level. However, existing approaches oft…
Going Denser with Open-Vocabulary Part Segmentation
Peize Sun, Shoufa Chen, Chenchen Zhu +4
Object detection has been expanded from a limited number of categories to open vocabulary. Moving forward, a complete intelligent vision system requires understanding more fine-gra…
Decoupling Representation and Classifier for Long-Tailed Recognition
Bingyi Kang, Saining Xie, Marcus Rohrbach +4
The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem. Existing solutions…
Only Time Can Tell: Discovering Temporal Data for Temporal Modeling
Laura Sevilla-Lara, Shengxin Zha, Zhicheng Yan +3
Understanding temporal information and how the visual world changes over time is a fundamental ability of intelligent systems. In video understanding, temporal information is at th…
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Yunpeng Chen, Haoqi Fan, Bing Xu +5
In natural images, information is conveyed at different frequencies where higher frequencies are usually encoded with fine details and lower frequencies are usually encoded with gl…
DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition
Zheng Shou, Xudong Lin, Yannis Kalantidis +4
Motion has shown to be useful for video understanding, where motion is typically represented by optical flow. However, computing flow from video frames is very time-consuming. Rece…
Graph-Based Global Reasoning Networks
Yunpeng Chen, Marcus Rohrbach, Zhicheng Yan +3
Globally modeling and reasoning over relations between regions can be beneficial for many computer vision tasks on both images and videos. Convolutional Neural Networks (CNNs) exce…
HACS: Human Action Clips and Segments Dataset for Recognition and Temporal Localization
Hang Zhao, Antonio Torralba, Lorenzo Torresani +1
This paper presents a new large-scale dataset for recognition and temporal localization of human actions collected from Web videos. We refer to it as HACS (Human Action Clips and S…
Learning Concept Taxonomies from Multi-modal Data
Hao Zhang, Zhiting Hu, Yuntian Deng +3
We study the problem of automatically building hypernym taxonomies from textual and visual data. Previous works in taxonomy induction generally ignore the increasingly prominent vi…
Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation
Zhicheng Yan, Hao Zhang, Yangqing Jia +2
State-of-the-art results of semantic segmentation are established by Fully Convolutional neural Networks (FCNs). FCNs rely on cascaded convolutional and pooling layers to gradually…
Automatic Photo Adjustment Using Deep Neural Networks
Zhicheng Yan, Hao Zhang, Baoyuan Wang +2
Photo retouching enables photographers to invoke dramatic visual impressions by artistically enhancing their photos through stylistic color and tone adjustments. However, it is als…
HD-CNN: Hierarchical Deep Convolutional Neural Network for Large Scale Visual Recognition
Zhicheng Yan, Hao Zhang, Robinson Piramuthu +4
In image classification, visual separability between different object categories is highly uneven, and some categories are more difficult to distinguish than others. Such difficult…