A causal diffusion model reconstructs videos from ultra-low-bitrate semantics and compressed frames using temporal distillation from a bidirectional teacher, outperforming prior baselines.
The cityscapes dataset for semantic urban scene understanding,
3 Pith papers cite this work. Polarity classification is still indexing.
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A unified imaging model and weather-prior network restores scenes across multiple adverse conditions by estimating occlusion and transmission from physical particle and scattering effects.
ROVR is a new diverse depth dataset for autonomous driving with 200K frames, released pipelines, and ablations showing sparse ground truth supports model training.
citing papers explorer
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A Causal Diffusion Model for Video Reconstruction from Ultra-Low-Bitrate Representations
A causal diffusion model reconstructs videos from ultra-low-bitrate semantics and compressed frames using temporal distillation from a bidirectional teacher, outperforming prior baselines.
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Unifying Physically-Informed Weather Priors in A Single Model for Image Restoration Across Multiple Adverse Weather Conditions
A unified imaging model and weather-prior network restores scenes across multiple adverse conditions by estimating occlusion and transmission from physical particle and scattering effects.
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ROVR-Open-Dataset: A Large-Scale Depth Dataset for Autonomous Driving
ROVR is a new diverse depth dataset for autonomous driving with 200K frames, released pipelines, and ablations showing sparse ground truth supports model training.