A differentiable motion forecasting model retrieves and refines interpretable trajectory anchors from a contrastively learned motion bank to improve transparency without sacrificing multi-modal accuracy.
An image is worth 16x16 words: Transformers for image recognition at scale, 2021
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Med-CAM generates minimal evidence masks for medical image classification by training a segmentation network to match classifier activations.
citing papers explorer
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Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank
A differentiable motion forecasting model retrieves and refines interpretable trajectory anchors from a contrastively learned motion bank to improve transparency without sacrificing multi-modal accuracy.
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Med-CAM: Minimal Evidence for Explaining Medical Decision Making
Med-CAM generates minimal evidence masks for medical image classification by training a segmentation network to match classifier activations.