4 papers
TrajLoom: Dense Future Trajectory Generation from Video
Zewei Zhang, Jia Jun Cheng Xian, Kaiwen Liu +4
Predicting future motion is crucial in video understanding and controllable video generation. Dense point trajectories are a compact, expressive motion representation, but modeling…
ControlEchoSynth: Boosting Ejection Fraction Estimation Models via Controlled Video Diffusion
Nima Kondori, Hanwen Liang, Hooman Vaseli +5
Synthetic data generation represents a significant advancement in boosting the performance of machine learning (ML) models, particularly in fields where data acquisition is challen…
QDM: Quadtree-Based Region-Adaptive Sparse Diffusion Models for Efficient Image Super-Resolution
Donglin Yang, Paul Vicol, Xiaojuan Qi +2
Deep learning-based super-resolution (SR) methods often perform pixel-wise computations uniformly across entire images, even in homogeneous regions where high-resolution refinement…
SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups
Yongxing Zhang, Donglin Yang, Renjie Liao
Finite symmetric groups are essential in fields such as combinatorics, physics, and chemistry. However, learning a probability distribution over poses significant chall…