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Found 4 papers, 3 papers with code
Improving Visual Recognition with Hyperbolical Visual Hierarchy Mapping
Visual scenes are naturally organized in a hierarchy, where a coarse semantic is recursively comprised of several fine details.
Knowing Where to Focus: Event-aware Transformer for Video Grounding
Recent DETR-based video grounding models have made the model directly predict moment timestamps without any hand-crafted components, such as a pre-defined proposal or non-maximum suppression, by learning moment queries.
Semantic-aware Network for Aerial-to-Ground Image Synthesis
Aerial-to-ground image synthesis is an emerging and challenging problem that aims to synthesize a ground image from an aerial image.
Probabilistic Prompt Learning for Dense Prediction
Recent progress in deterministic prompt learning has become a promising alternative to various downstream vision tasks, enabling models to learn powerful visual representations with the help of pre-trained vision-language models.
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