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Found 4 papers, 3 papers with code
A Foundation Model for Cell Segmentation
Methods that have learned the general notion of "what is a cell" and can identify them across different domains of cellular imaging data have proven elusive.
Text-image Alignment for Diffusion-based Perception
Our cross-domain segmentation method, trained on Cityscapes, achieves SOTA results on Dark Zurich-val and Nighttime Driving.
Ranked #1 on
Semantic Segmentation
on Nighttime Driving
MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior
We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations.
Robust Disentanglement of a Few Factors at a Time
Disentanglement is at the forefront of unsupervised learning, as disentangled representations of data improve generalization, interpretability, and performance in downstream tasks.
