ActDiff-VC achieves up to 64.6% bitrate reduction at matched NIQE and improves perceptual metrics like KID and FID by using content-adaptive keyframe selection and budget-aware sparse trajectory selection to condition a diffusion decoder for ultra-low-bitrate video reconstruction.
The thrity-seventh asilomar conference on signals, systems & computers, 2003 , volume=
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SynthRAD2025 shows deep learning produces synthetic CTs with MAE 48-65 HU and high dosimetric gamma passing rates for radiotherapy, performing better on CBCT-to-CT than MRI-to-CT tasks.
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Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusion
ActDiff-VC achieves up to 64.6% bitrate reduction at matched NIQE and improves perceptual metrics like KID and FID by using content-adaptive keyframe selection and budget-aware sparse trajectory selection to condition a diffusion decoder for ultra-low-bitrate video reconstruction.
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Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report
SynthRAD2025 shows deep learning produces synthetic CTs with MAE 48-65 HU and high dosimetric gamma passing rates for radiotherapy, performing better on CBCT-to-CT than MRI-to-CT tasks.
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