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Found 5 papers, 3 papers with code
Recognize Any Regions
Understanding the semantics of individual regions or patches within unconstrained images, such as in open-world object detection, represents a critical yet challenging task in computer vision.
Self-supervised Video Representation Learning with Motion-Aware Masked Autoencoders
As a result, our model can extract effectively both static appearance and dynamic motion spontaneously, leading to superior spatiotemporal representation learning capability.
MetaFormer: A Unified Meta Framework for Fine-Grained Recognition
Fine-Grained Visual Classification(FGVC) is the task that requires recognizing the objects belonging to multiple subordinate categories of a super-category.
Ranked #1 on
Fine-Grained Image Classification
on NABirds
(using extra training data)
Unbiased Scene Graph Generation via Rich and Fair Semantic Extraction
Extracting graph representation of visual scenes in image is a challenging task in computer vision.
An extended description logic system with knowledge element based on ALC
With the rise of knowledge management and knowledge economy, the knowledge elements that directly link and embody the knowledge system have become the research focus and hotspot in certain areas.
