Search Results for author:
Found 7 papers, 4 papers with code
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance Pursuit
The ability of scale-equivariance processing blocks plays a central role in arbitrary-scale image super-resolution tasks.
Learning Continuous Depth Representation via Geometric Spatial Aggregator
Depth map super-resolution (DSR) has been a fundamental task for 3D computer vision.
Im2Oil: Stroke-Based Oil Painting Rendering with Linearly Controllable Fineness Via Adaptive Sampling
Comparison with existing state-of-the-art oil painting techniques shows that our results have higher fidelity and more realistic textures.
Data Streaming and Traffic Gathering in Mesh-based NoC for Deep Neural Network Acceleration
In this paper, we propose a modified mesh architecture with a one-way/two-way streaming bus to speedup one-to-many (multicast) traffic, and the use of gather packets to support many-to-one (gather) traffic.
Improving the Performance of a NoC-based CNN Accelerator with Gather Support
For many-to-one traffic, repetitive unicast is employed which is not an efficient way.
Sketch Generation with Drawing Process Guided by Vector Flow and Grayscale
Existing pencil sketch algorithms are based on texture rendering rather than the direct imitation of strokes, making them unable to show the drawing process but only a final result.
DATE: Defense Against TEmperature Side-Channel Attacks in DVFS Enabled MPSoCs
Given the constant rise in utilizing embedded devices in daily life, side channels remain a challenge to information flow control and security in such systems.
