2 citations · 2 across the 4 of their papers we have counts for
4 papers
AnyFlow: Arbitrary Scale Optical Flow with Implicit Neural Representation
Hyunyoung Jung, Zhuo Hui, Lei Luo +5
To apply optical flow in practice, it is often necessary to resize the input to smaller dimensions in order to reduce computational costs. However, downsizing inputs makes the esti…
Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation
Hyunyoung Jung, Eunhyeok Park, Sungjoo Yoo
Self-supervised monocular depth estimation has been widely studied, owing to its practical importance and recent promising improvements. However, most works suffer from limited sup…
How Compact?: Assessing Compactness of Representations through Layer-Wise Pruning
Hyun-Joo Jung, Jaedeok Kim, Yoonsuck Choe
Various forms of representations may arise in the many layers embedded in deep neural networks (DNNs). Of these, where can we find the most compact representation? We propose to us…
Comparing Sample-wise Learnability Across Deep Neural Network Models
Seung-Geon Lee, Jaedeok Kim, Hyun-Joo Jung +1
Estimating the relative importance of each sample in a training set has important practical and theoretical value, such as in importance sampling or curriculum learning. This kind…