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Found 7 papers, 4 papers with code
Distributed Graph Embedding with Information-Oriented Random Walks
Graph embedding maps graph nodes to low-dimensional vectors, and is widely adopted in machine learning tasks.
MALICE: Manipulation Attacks on Learned Image ComprEssion
To characterize the robustness of state-of-the-art learned image compression, we mount white-box and black-box attacks.
Convolutional Neural Network for Universal Sentence Embeddings
This paper proposes a simple CNN model for creating general-purpose sentence embeddings that can transfer easily across domains and can also act as effective initialization for downstream tasks.
Benchmarking Single Image Dehazing and Beyond
We present a comprehensive study and evaluation of existing single image dehazing algorithms, using a new large-scale benchmark consisting of both synthetic and real-world hazy images, called REalistic Single Image DEhazing (RESIDE).
AOD-Net: All-In-One Dehazing Network
This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net).
Ranked #20 on
Image Dehazing
on SOTS Outdoor
End-to-End United Video Dehazing and Detection
Furthermore, we build an End-to-End United Video Dehazing and Detection Network(EVDD-Net), which concatenates and jointly trains EVD-Net with a video object detection model.
An All-in-One Network for Dehazing and Beyond
This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net).
