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Found 5 papers, 1 papers with code
Customizing Segmentation Foundation Model via Prompt Learning for Instance Segmentation
Recently, foundation models trained on massive datasets to adapt to a wide range of domains have attracted considerable attention and are actively being explored within the computer vision community.
Adversarial Training with Stochastic Weight Average
Moreover, we further improved SWA to be adequate to adversarial training.
Localization Uncertainty Estimation for Anchor-Free Object Detection
To tackle these limitations, we propose a new localization uncertainty estimation method called UAD for anchor-free object detection.
Ranked #116 on
Object Detection
on COCO test-dev
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
As DenseNet conserves intermediate features with diverse receptive fields by aggregating them with dense connection, it shows good performance on the object detection task.
Ranked #64 on
Instance Segmentation
on COCO test-dev
Rank of Experts: Detection Network Ensemble
The recent advances of convolutional detectors show impressive performance improvement for large scale object detection.
