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Found 8 papers, 6 papers with code
CLOAF: CoLlisiOn-Aware Human Flow
Even the best current algorithms for estimating body 3D shape and pose yield results that include body self-intersections.
CLIP the Gap: A Single Domain Generalization Approach for Object Detection
Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain.
Learning Transformations To Reduce the Geometric Shift in Object Detection
The performance of modern object detectors drops when the test distribution differs from the training one.
Multi-view Tracking Using Weakly Supervised Human Motion Prediction
Multi-view approaches to people-tracking have the potential to better handle occlusions than single-view ones in crowded scenes.
Ranked #2 on
Multi-Object Tracking
on Wildtrack
Two-level Data Augmentation for Calibrated Multi-view Detection
Data augmentation has proven its usefulness to improve model generalization and performance.
SoDeep: a Sorting Deep net to learn ranking loss surrogates
Our approach is based on a deep architecture that approximates the sorting of arbitrary sets of scores.
VideoMem: Constructing, Analyzing, Predicting Short-term and Long-term Video Memorability
Humans share a strong tendency to memorize/forget some of the visual information they encounter.
Finding beans in burgers: Deep semantic-visual embedding with localization
Several works have proposed to learn a two-path neural network that maps images and texts, respectively, to a same shared Euclidean space where geometry captures useful semantic relationships.
