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Found 8 papers, 5 papers with code
Flow Guided Transformable Bottleneck Networks for Motion Retargeting
Human motion retargeting aims to transfer the motion of one person in a "driving" video or set of images to another person.
Motion Representations for Articulated Animation
To facilitate animation and prevent the leakage of the shape of the driving object, we disentangle shape and pose of objects in the region space.
Ranked #1 on
Video Reconstruction
on Tai-Chi-HD (512)
Teachers Do More Than Teach: Compressing Image-to-Image Models
In this work, we aim to address these issues by introducing a teacher network that provides a search space in which efficient network architectures can be found, in addition to performing knowledge distillation.
Separable Flow: Learning Motion Cost Volumes for Optical Flow Estimation
Full-motion cost volumes play a central role in current state-of-the-art optical flow methods.
Ranked #4 on
Optical Flow Estimation
on KITTI 2015 (train)
Progressive Batching for Efficient Non-linear Least Squares
Non-linear least squares solvers are used across a broad range of offline and real-time model fitting problems.
Large Scale Photometric Bundle Adjustment
Issues such as the lack of brightness constancy, and the sheer volume of data, make this a more challenging task.
Least Squares Normalized Cross Correlation
They have leveraged least squares minimizations, for simple, efficient, variational optimization, since the seminal 1981 work of Lucas & Kanade, and normalized cross correlation (NCC), for robustness to intensity variations, since at least 1972.
Noise Models in Feature-based Stereo Visual Odometry
Feature-based visual structure and motion reconstruction pipelines, common in visual odometry and large-scale reconstruction from photos, use the location of corresponding features in different images to determine the 3D structure of the scene, as well as the camera parameters associated with each image.
