3 citations · 7 across the 11 of their papers we have counts for
11 papers
Perfecting Depth: Uncertainty-Aware Enhancement of Metric Depth
Jinyoung Jun, Lei Chu, Jiahao Li +2
We propose a novel two-stage framework for sensor depth enhancement, called Perfecting Depth. This framework leverages the stochastic nature of diffusion models to automatically de…
OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection
Dongkwon Jin, Chang-Su Kim
A novel algorithm for video lane detection is proposed in this paper. First, we extract a feature map for a current frame and detect a latent mask for obstacles occluding lanes. Th…
Masked Spatial Propagation Network for Sparsity-Adaptive Depth Refinement
Jinyoung Jun, Jae-Han Lee, Chang-Su Kim
The main function of depth completion is to compensate for an insufficient and unpredictable number of sparse depth measurements of hardware sensors. However, existing research on…
Clicks2Line: Using Lines for Interactive Image Segmentation
Chaewon Lee, Chang-Su Kim
For click-based interactive segmentation methods, reducing the number of clicks required to obtain a desired segmentation result is essential. Although recent click-based methods y…
Recursive Video Lane Detection
Dongkwon Jin, Dahyun Kim, Chang-Su Kim
A novel algorithm to detect road lanes in videos, called recursive video lane detector (RVLD), is proposed in this paper, which propagates the state of a current frame recursively…
BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation
Junheum Park, Jintae Kim, Chang-Su Kim
A novel 4K video frame interpolator based on bilateral transformer (BiFormer) is proposed in this paper, which performs three steps: global motion estimation, local motion refineme…