Weakly Supervised Object Detection (WSOD) is the task of training object detectors with only image tag supervisions.
( Image credit: Soft Proposal Networks for Weakly Supervised Object Localization )
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Can we detect common objects in a variety of image domains without instance-level annotations?
Ranked #1 on Weakly Supervised Object Detection on Watercolor2k (using extra training data)
Weakly supervised object localization remains challenging, where only image labels instead of bounding boxes are available during training.
Ranked #2 on Weakly Supervised Object Detection on COCO
The iterative instance classifier refinement is implemented online using multiple streams in convolutional neural networks, where the first is an MIL network and the others are for instance classifier refinement supervised by the preceding one.
Ranked #1 on Weakly Supervised Object Detection on ImageNet
We propose a novel online instance classifier refinement algorithm to integrate MIL and the instance classifier refinement procedure into a single deep network, and train the network end-to-end with only image-level supervision, i. e., without object location information.
Ranked #4 on Weakly Supervised Object Detection on ImageNet
Weakly supervised learning of object detection is an important problem in image understanding that still does not have a satisfactory solution.
Ranked #3 on Weakly Supervised Object Detection on HICO-DET
In the source domain, we fully train an object detector and the RRPN with full supervision of HOI.
Weakly supervised learning has emerged as a compelling tool for object detection by reducing the need for strong supervision during training.
Ranked #1 on Weakly Supervised Object Detection on COCO test-dev
The additive model encourages the predicted object region to be supported by its surrounding context region.
Ranked #4 on Weakly Supervised Object Detection on Charades
Weakly supervised object detection (WSOD) is a challenging task when provided with image category supervision but required to simultaneously learn object locations and object detectors.
Weakly supervised object detection (WSOD) using only image-level annotations has attracted growing attention over the past few years.