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06/29/2023
An Efficient General-Purpose Modular Vision Model via Multi-Task Heterogeneous Training
We present a model that can perform multiple vision tasks and can be ada...
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04/06/2023
Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention
Humans possess a versatile mechanism for extracting structured represent...
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12/15/2022
Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners
Optimization in multi-task learning (MTL) is more challenging than singl...
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04/01/2021
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study
This work aims to empirically clarify a recently discovered perspective ...
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10/06/2020
Shot in the Dark: Few-Shot Learning with No Base-Class Labels
Few-shot learning aims to learn classifiers for new objects from a small...
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06/26/2020
Cross-Ssupervised Object Detection
After learning a new object category from image-level annotations (with ...
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06/26/2020
Cross-Supervised Object Detection
After learning a new object category from image-level annotations (with ...
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05/28/2019
Image Deformation Meta-Networks for One-Shot Learning
Humans can robustly learn novel visual concepts even when images undergo...
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09/23/2018
Neural Arithmetic Expression Calculator
This paper presents a pure neural solver for arithmetic expression calcu...
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04/15/2018
Semantic Feature Augmentation in Few-shot Learning
A fundamental problem with few-shot learning is the scarcity of data in ...
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02/08/2018