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20102022
most citedRecent Advances in Convolutional Neural Networks

325 citations · 2k across the 89 of their papers we have counts for

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Showing 2017Show all

9 papers · 1 filter

cs.CV2017★ 4 cited

Zero-Shot Learning via Category-Specific Visual-Semantic Mapping

Li Niu, Jianfei Cai, Ashok Veeraraghavan

Zero-Shot Learning (ZSL) aims to classify a test instance from an unseen category based on the training instances from seen categories, in which the gap between seen categories and…

cs.CV2017★ 37 cited

Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models

Jiuxiang Gu, Jianfei Cai, Shafiq Joty +2

Textual-visual cross-modal retrieval has been a hot research topic in both computer vision and natural language processing communities. Learning appropriate representations for mul…

cs.CV2017★ 4 cited

Zero-Annotation Object Detection with Web Knowledge Transfer

Qingyi Tao, Hao Yang, Jianfei Cai

Object detection is one of the major problems in computer vision, and has been extensively studied. Most of the existing detection works rely on labor-intensive supervision, such a…

cs.CV2017★ 58 cited

Stack-Captioning: Coarse-to-Fine Learning for Image Captioning

Jiuxiang Gu, Jianfei Cai, Gang Wang +1

The existing image captioning approaches typically train a one-stage sentence decoder, which is difficult to generate rich fine-grained descriptions. On the other hand, multi-stage…

cs.CV2017★ 5 cited

CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images

Yudong Guo, Juyong Zhang, Jianfei Cai +2

With the powerfulness of convolution neural networks (CNN), CNN based face reconstruction has recently shown promising performance in reconstructing detailed face shape from 2D fac…

cs.CV2017★ 5 cited

Exploiting Web Images for Weakly Supervised Object Detection

Qingyi Tao, Hao Yang, Jianfei Cai

In recent years, the performance of object detection has advanced significantly with the evolving deep convolutional neural networks. However, the state-of-the-art object detection…