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AMS-Net: Modeling adaptive multi-granularity spatio-temporal cues for video action recognition
Effective spatio-temporal modeling as a core of video representation learning is challenged
by complex scale variations in spatio-temporal cues in videos, especially different visual …
by complex scale variations in spatio-temporal cues in videos, especially different visual …
Learning from untrimmed videos: Self-supervised video representation learning with hierarchical consistency
Natural videos provide rich visual contents for self-supervised learning. Yet most existing
approaches for learning spatio-temporal representations rely on manually trimmed videos …
approaches for learning spatio-temporal representations rely on manually trimmed videos …
Highlighting object category immunity for the generalization of human-object interaction detection
Abstract Human-Object Interaction (HOI) detection plays a core role in activity
understanding. As a compositional learning problem (human-verb-object), studying its …
understanding. As a compositional learning problem (human-verb-object), studying its …
Self-supervised learning from untrimmed videos via hierarchical consistency
Natural untrimmed videos provide rich visual content for self-supervised learning. Yet most
previous efforts to learn spatio-temporal representations rely on manually trimmed videos …
previous efforts to learn spatio-temporal representations rely on manually trimmed videos …
Shifted gcn-gat and cumulative-transformer based social relation recognition for long videos
Social Relation Recognition is an important part of Video Understanding, providing insights
into the information that videos convey. Most previous works mainly focused on graph …
into the information that videos convey. Most previous works mainly focused on graph …
Markov Progressive Framework, a Universal Paradigm for Modeling Long Videos
The computational complexity of video models increases linearly with the square number of
frames. Thus, constrained bycomputational resources, training video models to learn long …
frames. Thus, constrained bycomputational resources, training video models to learn long …
High-order correlation network for video recognition
How to model global video representation is an important research content of video
recognition. Among current convolutional neural network (CNN) based methods, only using …
recognition. Among current convolutional neural network (CNN) based methods, only using …
Enhancing Video Understanding: Deep Neural Networks for Spatiotemporal Analysis
AH Fadaei, MRA Dehaqani - ar** end-to-end action recognition models on long videos is fundamental and crucial
for long-video action understanding. Due to the unaffordable cost of end-to-end training on …
for long-video action understanding. Due to the unaffordable cost of end-to-end training on …