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Found 7 papers, 1 papers with code
GAN-EM: GAN based EM learning framework
To overcome such limitation, we propose a GAN based EM learning framework that can maximize the likelihood of images and estimate the latent variables with only the constraint of L-Lipschitz continuity.
How to Make a BLT Sandwich? Learning to Reason towards Understanding Web Instructional Videos
Furthermore, we study multiple modalities including description and transcripts for the purpose of boosting video understanding.
Weakly Supervised Localization Using Background Images
Weakly Supervised Object Localization (WSOL) methodsusually rely on fully convolutional networks in order to ob-tain class activation maps(CAMs) of targeted labels.
Improve CAM with Auto-adapted Segmentation and Co-supervised Augmentation
In this paper, we propose a confidence segmentation (ConfSeg) module that builds confidence score for each pixel in CAM without introducing additional hyper-parameters.
Adversarial Robustness of Deep Sensor Fusion Models
First, we find that the fusion model is usually both more accurate, and more robust against single-source attacks than single-sensor deep neural networks.
PROVES: Establishing Image Provenance using Semantic Signatures
Modern AI tools, such as generative adversarial networks, have transformed our ability to create and modify visual data with photorealistic results.
A bioinspired three-stage model for camouflaged object detection
Furthermore, considering the significance of multi-scale information, we have designed a multi-scale feature enhancement module that enlarges the receptive field while preserving detailed structural cues.
