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Found 4 papers, 1 papers with code
PointBeV: A Sparse Approach to BeV Predictions
To address this, we propose PointBeV, a novel sparse BeV segmentation model operating on sparse BeV cells instead of dense grids.
Context-Aware Zero-Shot Learning for Object Recognition
Zero-Shot Learning (ZSL) aims at classifying unlabeled objects by leveraging auxiliary knowledge, such as semantic representations.
Incorporating Visual Semantics into Sentence Representations within a Grounded Space
To overcome this limitation, we propose to transfer visual information to textual representations by learning an intermediate representation space: the grounded space.
Transductive Zero-Shot Learning using Cross-Modal CycleGAN
We show the efficiency of our Cross-Modal CycleGAN model (CM-GAN) on the ImageNet T-ZSL task where we obtain state-of-the-art results.
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