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20182026
most citedImage Deformation Meta-Networks for One-Shot Learning

23 citations · 27 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

Efficient Visual Question Answering Pipeline for Autonomous Driving via Scene Region Compression

Yuliang Cai, Dongqiangzi Ye, Zitian Chen +1

Autonomous driving increasingly relies on Visual Question Answering (VQA) to enable vehicles to understand complex surroundings by analyzing visual inputs and textual queries. Curr…

cs.CV2020

Shot in the Dark: Few-Shot Learning with No Base-Class Labels

Zitian Chen, Subhransu Maji, Erik Learned-Miller

Few-shot learning aims to build classifiers for new classes from a small number of labeled examples and is commonly facilitated by access to examples from a distinct set of 'base c…

cs.CV20204 cited

Cross-Supervised Object Detection

Zitian Chen, Zhiqiang Shen, Jiahui Yu +1

After learning a new object category from image-level annotations (with no object bounding boxes), humans are remarkably good at precisely localizing those objects. However, buildi…

cs.CV201923 cited

Image Deformation Meta-Networks for One-Shot Learning

Zitian Chen, Yanwei Fu, Yu-Xiong Wang +3

Humans can robustly learn novel visual concepts even when images undergo various deformations and lose certain information. Mimicking the same behavior and synthesizing deformed in…

cs.CV2018

Multi-level Semantic Feature Augmentation for One-shot Learning

Zitian Chen, Yanwei Fu, Yinda Zhang +3

The ability to quickly recognize and learn new visual concepts from limited samples enables humans to swiftly adapt to new environments. This ability is enabled by semantic associa…