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09/15/2023
Breathing New Life into 3D Assets with Generative Repainting
Diffusion-based text-to-image models ignited immense attention from the ...
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10/13/2022
Composite Learning for Robust and Effective Dense Predictions
Multi-task learning promises better model generalization on a target tas...
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03/07/2022
ZippyPoint: Fast Interest Point Detection, Description, and Matching through Mixed Precision Discretization
The design of more complex and powerful neural network models has signif...
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12/17/2021
Efficient Visual Tracking with Exemplar Transformers
The design of more complex and powerful neural network models has signif...
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05/17/2021
Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation
We present an approach for encoding visual task relationships to improve...
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04/28/2021
Exploring Relational Context for Multi-Task Dense Prediction
The timeline of computer vision research is marked with advances in lear...
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08/24/2020
Automated Search for Resource-Efficient Branched Multi-Task Networks
The multi-modal nature of many vision problems calls for neural network ...
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07/24/2020
Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference
Multi-task networks are commonly utilized to alleviate the need for a la...
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07/13/2020
T-Basis: a Compact Representation for Neural Networks
We introduce T-Basis, a novel concept for a compact representation of a ...
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12/15/2019
