105 citations · 394 across the 23 of their papers we have counts for
5 papers · 1 filter
Accelerating GMM-based patch priors for image restoration: Three ingredients for a 100 speed-up
Shibin Parameswaran, Charles-Alban Deledalle, Loïc Denis +1
Image restoration methods aim to recover the underlying clean image from corrupted observations. The Expected Patch Log-likelihood (EPLL) algorithm is a powerful image restoration…
Camera-Aware Multi-Resolution Analysis (CAMRA) for Raw Sensor Data Compression
Y. Lee, K. Hirakawa, T. Nguyen
We propose a novel lossless and lossy compression scheme for color filter array~(CFA) sampled images based on the wavelet transform of them. Our analysis suggests that the wavelet…
Depth Adaptive Deep Neural Network for Semantic Segmentation
Byeongkeun Kang, Yeejin Lee, Truong Q. Nguyen
In this work, we present the depth-adaptive deep neural network using a depth map for semantic segmentation. Typical deep neural networks receive inputs at the predetermined locati…
LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems
Subarna Tripathi, Gokce Dane, Byeongkeun Kang +2
Deep convolutional Neural Networks (CNN) are the state-of-the-art performers for object detection task. It is well known that object detection requires more computation and memory…
Relevance Subject Machine: A Novel Person Re-identification Framework
Igor Fedorov, Ritwik Giri, Bhaskar D. Rao +1
We propose a novel method called the Relevance Subject Machine (RSM) to solve the person re-identification (re-id) problem. RSM falls under the category of Bayesian sparse recovery…