Gaflow: Incorporating gaussian attention into optical flow
Optical flow, or the estimation of motion fields from image sequences, is one of the
fundamental problems in computer vision. Unlike most pixel-wise tasks that aim at achieving …
fundamental problems in computer vision. Unlike most pixel-wise tasks that aim at achieving …
Supervised homography learning with realistic dataset generation
In this paper, we propose an iterative framework, which consists of two phases: a generation
phase and a training phase, to generate realistic training data and yield a supervised …
phase and a training phase, to generate realistic training data and yield a supervised …
Dmhomo: Learning homography with diffusion models
Supervised homography estimation methods face a challenge due to the lack of adequate
labeled training data. To address this issue, we propose DMHomo, a diffusion model-based …
labeled training data. To address this issue, we propose DMHomo, a diffusion model-based …
Single image rolling shutter removal with diffusion models
Blind 3D Video Stabilization with Spatio-Temporally Varying Motion Blur
Video stabilization is a challenging task that attempts to compensate for the overall frame
shake during video acquisition. Existing three-dimensional video stabilization methods aim …
shake during video acquisition. Existing three-dimensional video stabilization methods aim …
FlowDA: Unsupervised Domain Adaptive Framework for Optical Flow Estimation
[PDF][PDF] Robust Unsupervised Optical Flow Under Low-Visibility Conditions
L Long, T Liu, R Laganière, J Lang - vcad-workshop.github.io
Although state-of-the-art unsupervised optical flow methods achieve impressive results in
clean scenes, they still struggle under lowvisibility weather and illumination. However …
clean scenes, they still struggle under lowvisibility weather and illumination. However …