BAGEL
A diffusion-based multi-view generation architecture that treats multi-view generation as a sequential view synthesis process and uses attention mechanisms to transfer information between views. Its weights are open-source.
Timeline (last 90 days)
After fine-tuning on the MindView training set, BAGEL's overall score improved by 24.3 points.
The fine-tuned BAGEL shows gains on all seven tasks.
The fine-tuned BAGEL also achieved higher scores on three spatial understanding benchmarks, even though it was not trained on annotations from these benchmarks.
BAGEL is a diffusion-model-based multi-view generation architecture that treats multi-view generation as a serialized view synthesis process and uses attention mechanisms to pass information between views.
Learning to generate spatially grounded views may in turn enhance spatial understanding, indicating positive transfer between generation and understanding.
All Facts (5)
After fine-tuning on the MindView training set, BAGEL's overall score improved by 24.3 points.
50%UnverifiedThe fine-tuned BAGEL shows gains on all seven tasks.
50%UnverifiedThe fine-tuned BAGEL also achieved higher scores on three spatial understanding benchmarks, even though it was not trained on annotations from these benchmarks.
50%UnverifiedBAGEL is a diffusion-model-based multi-view generation architecture that treats multi-view generation as a serialized view synthesis process and uses attention mechanisms to pass information between views.
50%UnverifiedLearning to generate spatially grounded views may in turn enhance spatial understanding, indicating positive transfer between generation and understanding.
50%