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08/24/2023
Label Budget Allocation in Multi-Task Learning
The cost of labeling data often limits the performance of machine learni...
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08/03/2023
DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition with Limited Annotations
Multi-label image recognition in the low-label regime is a task of great...
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03/31/2023
DIME-FM: DIstilling Multimodal and Efficient Foundation Models
Large Vision-Language Foundation Models (VLFM), such as CLIP, ALIGN and ...
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06/20/2022
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations
Solving multi-label recognition (MLR) for images in the low-label regime...
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08/23/2021
Dynamic Network Quantization for Efficient Video Inference
Deep convolutional networks have recently achieved great success in vide...
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05/11/2021
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
Multi-modal learning, which focuses on utilizing various modalities to i...
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03/02/2021
All at Once Network Quantization via Collaborative Knowledge Transfer
Network quantization has rapidly become one of the most widely used meth...
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03/31/2020
Revisiting Few-shot Activity Detection with Class Similarity Control
Many interesting events in the real world are rare making preannotated m...
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11/27/2019
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
Multi-task learning is an open and challenging problem in computer visio...
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06/11/2019
Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition
Learning from a few examples is a challenging task for machine learning....
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04/28/2019
Domain Agnostic Learning with Disentangled Representations
Unsupervised model transfer has the potential to greatly improve the gen...
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12/25/2018
Similarity R-C3D for Few-shot Temporal Activity Detection
Many activities of interest are rare events, with only a few labeled exa...
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12/03/2018
A Two-Stream Variational Adversarial Network for Video Generation
Video generation is an inherently challenging task, as it requires the m...
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03/20/2018
