Transfer learning enhanced vision-based human activity recognition: a decade-long analysis
The discovery of several machine learning and deep learning techniques has paved the
way to extend the reach of humans in various real-world applications. Classical machine …
way to extend the reach of humans in various real-world applications. Classical machine …
Recent advances in zero-shot recognition: Toward data-efficient understanding of visual content
Y Fu, T ** network
Instance-level human parsing towards real-world human analysis scenarios is still under-
explored due to the absence of sufficient data resources and technical difficulty in parsing …
explored due to the absence of sufficient data resources and technical difficulty in parsing …
Look into person: Joint body parsing & pose estimation network and a new benchmark
Human parsing and pose estimation have recently received considerable interest due to
their substantial application potentials. However, the existing datasets have limited numbers …
their substantial application potentials. However, the existing datasets have limited numbers …
Look into person: Self-supervised structure-sensitive learning and a new benchmark for human parsing
Human parsing has recently attracted a lot of research interests due to its huge application
potentials. However existing datasets have limited number of images and annotations, and …
potentials. However existing datasets have limited number of images and annotations, and …
Elaborative rehearsal for zero-shot action recognition
The growing number of action classes has posed a new challenge for video understanding,
making Zero-Shot Action Recognition (ZSAR) a thriving direction. The ZSAR task aims to …
making Zero-Shot Action Recognition (ZSAR) a thriving direction. The ZSAR task aims to …
Semantic object parsing with graph lstm
By taking the semantic object parsing task as an exemplar application scenario, we propose
the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of …
the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of …
I know the relationships: Zero-shot action recognition via two-stream graph convolutional networks and knowledge graphs
Recently, with the ever-growing action categories, zero-shot action recognition (ZSAR) has
been achieved by automatically mining the underlying concepts (eg, actions, attributes) in …
been achieved by automatically mining the underlying concepts (eg, actions, attributes) in …
Two-stream 3-d convnet fusion for action recognition in videos with arbitrary size and length
3-D convolutional neural networks (3-D-convNets) have been very recently proposed for
action recognition in videos, and promising results are achieved. However, existing 3-D …
action recognition in videos, and promising results are achieved. However, existing 3-D …
Rethinking zero-shot video classification: End-to-end training for realistic applications
Trained on large datasets, deep learning (DL) can accurately classify videos into hundreds
of diverse classes. However, video data is expensive to annotate. Zero-shot learning (ZSL) …
of diverse classes. However, video data is expensive to annotate. Zero-shot learning (ZSL) …