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Found 8 papers, 7 papers with code
Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation
We view this work as a notable step towards building a simple procedure to harness unlabeled video sequences and extra images to surpass state-of-the-art performance on core computer vision tasks.
A Fourier Perspective on Model Robustness in Computer Vision
Achieving robustness to distributional shift is a longstanding and challenging goal of computer vision.
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation
Deploying machine learning systems in the real world requires both high accuracy on clean data and robustness to naturally occurring corruptions.
A Learned Representation for Scalable Vector Graphics
Dramatic advances in generative models have resulted in near photographic quality for artificially rendered faces, animals and other objects in the natural world.
End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features
We introduce a new dataset of dialogs about videos of human behaviors.
Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7
Scene-aware dialog systems will be able to have conversations with users about the objects and events around them.
Data-Free Knowledge Distillation for Deep Neural Networks
Recent advances in model compression have provided procedures for compressing large neural networks to a fraction of their original size while retaining most if not all of their accuracy.
