CAFOSat is a new strongly annotated remote-sensing dataset for CAFO mapping that uses human-in-the-loop refinement and curated negatives, with benchmarks on CNNs, transformers, and vision-language models plus a synthetic augmentation pipeline.
Video probabilistic diffusion models in projected latent space
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Introduces 9 synthetic annotation tasks and benchmarks for behavioral cloning, finding hierarchical skill learning, scaling benefits, effective multi-task pretraining, and shared internal representations of task phases and mistakes.
Latent-space hierarchical diffusion models with targeted error-correction techniques generate realistic videos exceeding 1000 frames while using less compute than prior pixel-space approaches.
citing papers explorer
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CAFOSat: A Strongly Annotated Dataset for Infrastructure-Aware CAFO Mapping Using High-Resolution Imagery
CAFOSat is a new strongly annotated remote-sensing dataset for CAFO mapping that uses human-in-the-loop refinement and curated negatives, with benchmarks on CNNs, transformers, and vision-language models plus a synthetic augmentation pipeline.
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A Systematic Study of Behavioral Cloning for Scientific Data Annotation
Introduces 9 synthetic annotation tasks and benchmarks for behavioral cloning, finding hierarchical skill learning, scaling benefits, effective multi-task pretraining, and shared internal representations of task phases and mistakes.
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Latent Video Diffusion Models for High-Fidelity Long Video Generation
Latent-space hierarchical diffusion models with targeted error-correction techniques generate realistic videos exceeding 1000 frames while using less compute than prior pixel-space approaches.