Adds a block that predicts state variables (velocity, acceleration) to seq2seq motion prediction models
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Updated
Mar 11, 2018 - Python
Adds a block that predicts state variables (velocity, acceleration) to seq2seq motion prediction models
Re-running some analysis on the 2019 RO introspection paper.
Initially focused on landmark distortion effects, and evolved into leveraging a constant curvature constraint.
[ICCV 2023] Learning Fine-Grained Features for Pixel-wise Video Correspondences
Continuous Estimation of Human Joint Angles From sEMG Using a Multi-Feature Temporal Convolutional Attention-Based Network
X-Metric: An N-Dimensional Information-Theoretic Framework for Groupwise Registration and Deep Combined Computing (TPAMI 2023)
[ECCV 2022 Oral] Source code for "A Perturbation-Constrained Adversarial Attack for Evaluating the Robustness of Optical Flow"
Synthesizing multi-mode handwriting motion with kinematics features
Blind deconvolution of motion blur
Kalman Filter Implementation for object tracking and motion estimation
Implementation of ChipQA (https://ieeexplore.ieee.org/document/9540785)
Event-based Background-Oriented Schlieren (T-PAMI 2023)
Implementation of PWOC-3D network for end-to-end stereo scene flow estimation
Sequence-to-sequence image and contour prediction library for longitudinal datasets [PMB'23]
Demo for "MoSculp: Interactive Visualization of Shape and Time"
[MICCAI'18] Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
Python implementation of Typhoon algorithm: dense estimation of 2D-3D optical flow on wavelet bases.
Motion R-CNN: Mask R-CNN with support for 3D motion estimation (prototype)
Optical Flow Dataset and Benchmark for Visual Crowd Analysis
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency (AAAI 2021)
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