Hierarchy-Aware Cross-Entropy improves image classification by incorporating class hierarchies into the loss through prediction aggregation and ancestral label smoothing, achieving mean accuracy gains of 4.66% in end-to-end training and 2.18% in linear probing.
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FFAvatar is a generalizable feed-forward framework that reconstructs high-quality animatable 3D Gaussian head avatars from few-shot unposed portrait images in seconds via Multi-View Query-Former and end-to-end FLAME prediction.
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When Labels Have Structure: Improving Image Classification with Hierarchy-Aware Cross-Entropy
Hierarchy-Aware Cross-Entropy improves image classification by incorporating class hierarchies into the loss through prediction aggregation and ancestral label smoothing, achieving mean accuracy gains of 4.66% in end-to-end training and 2.18% in linear probing.
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FFAvatar: Few-Shot, Feed-Forward, and Generalizable Avatar Reconstruction
FFAvatar is a generalizable feed-forward framework that reconstructs high-quality animatable 3D Gaussian head avatars from few-shot unposed portrait images in seconds via Multi-View Query-Former and end-to-end FLAME prediction.