Lossy common information in a learnable Gray-Wyner Network
Isolate the common information between two dependent computer vision tasks.
Computer Vision
Rate-distortion theory in coding for machines and its applications
Theoretical considerations and evaluation of split and distillation points.
Towards task-compatible compressible representations
Task reconstruction loss acts as a regularizer, increasing rate-distortion performance in coding for humans and machines.
Base layer efficiency in scalable human-machine coding
Improving the shared channel in coding for machines (CfM).
Conditional and residual methods in scalable coding for humans and machines
A comparison between conditional and residual entropy codecs for a two-channel systems of tasks with nested information.
Best practices for convolutional neural networks applied to object recognition in images
Evaluate the performance impact of optimization algorithms, activation functions, dropout, and maxout networks, in CNNs.