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Found 8 papers, 4 papers with code
PIN: Positional Insert Unlocks Object Localisation Abilities in VLMs
Vision-Language Models (VLMs), such as Flamingo and GPT-4V, have shown immense potential by integrating large language models with vision systems.
SCVRL: Shuffled Contrastive Video Representation Learning
We propose SCVRL, a novel contrastive-based framework for self-supervised learning for videos.
iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis
There will be distinctive movement, despite evident variations caused by the stochastic nature of our world.
Understanding Object Dynamics for Interactive Image-to-Video Synthesis
Given a static image of an object and a local poking of a pixel, the approach then predicts how the object would deform over time.
Stochastic Image-to-Video Synthesis using cINNs
Video understanding calls for a model to learn the characteristic interplay between static scene content and its dynamics: Given an image, the model must be able to predict a future progression of the portrayed scene and, conversely, a video should be explained in terms of its static image content and all the remaining characteristics not present in the initial frame.
Behavior-Driven Synthesis of Human Dynamics
Using this representation, we are able to change the behavior of a person depicted in an arbitrary posture, or to even directly transfer behavior observed in a given video sequence.
Unsupervised Behaviour Analysis and Magnification (uBAM) using Deep Learning
A central aspect is unsupervised learning of posture and behaviour representations to enable an objective comparison of movement.
Unsupervised Magnification of Posture Deviations Across Subjects
We present an approach to unsupervised magnification of posture differences across individuals despite large deviations in appearance.
