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Tips and Tricks for Webly-Supervised Fine-Grained Recognition: Learning from the WebFG 2020 Challenge
WebFG 2020 is an international challenge hosted by Nanjing University of...
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Field-wise Learning for Multi-field Categorical Data
We propose a new method for learning with multi-field categorical data. ...
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Data-driven Meta-set Based Fine-Grained Visual Classification
Constructing fine-grained image datasets typically requires domain-speci...
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Salvage Reusable Samples from Noisy Data for Robust Learning
Due to the existence of label noise in web images and the high memorizat...
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PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks
Despite significant progress of applying deep learning methods to the fi...
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Motion-Attentive Transition for Zero-Shot Video Object Segmentation
In this paper, we present a novel Motion-Attentive Transition Network (M...
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Extracting Visual Knowledge from the Internet: Making Sense of Image Data
Recent successes in visual recognition can be primarily attributed to fe...
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Dynamically Visual Disambiguation of Keyword-based Image Search
Due to the high cost of manual annotation, learning directly from the we...
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Deep Representation Learning for Road Detection through Siamese Network
Robust road detection is a key challenge in safe autonomous driving. Rec...
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Road Segmentation with Image-LiDAR Data Fusion
Robust road segmentation is a key challenge in self-driving research. Th...
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Towards Automatic Construction of Diverse, High-quality Image Dataset
The availability of labeled image datasets has been shown critical for h...
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Refining Image Categorization by Exploiting Web Images and General Corpus
Studies show that refining real-world categories into semantic subcatego...
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Exploiting Web Images for Dataset Construction: A Domain Robust Approach
Labelled image datasets have played a critical role in high-level image ...
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