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Found 7 papers, 0 papers with code
KCP: Kernel Cluster Pruning for Dense Labeling Neural Networks
We developed a clustering technique to identify the least representational kernels in each layer.
How to Exploit the Transferability of Learned Image Compression to Conventional Codecs
Recent research suggests that generative adversarial networks have the ability to overcome this limitation and serve as a multi-modal loss, especially for textures.
Joint Pruning & Quantization for Extremely Sparse Neural Networks
We investigate pruning and quantization for deep neural networks.
Utilising Low Complexity CNNs to Lift Non-Local Redundancies in Video Coding
The method can be applied to any existing video codec to increase coding gains while its low computational footprint allows for an application under resource-constrained conditions.
Dynamically Expanded CNN Array for Video Coding
Marked progress has been made in video quality, compression, and computational efficiency.
What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing
Our proposed two-stage integration more than halves the gap towards fully supervised methods when compared to previous state-of-the-art in transfer learning.
