Single-shot HDR is achieved by conditioning a video diffusion model on an LDR input to generate an exposure bracket and fusing the bracket with per-pixel weights from a lightweight UNet.
Hdr-vdp-3: A multi-metric for predicting image differences, quality and contrast distortions in high dynamic range and regular content.arXiv preprint arXiv:2304.13625
8 Pith papers cite this work. Polarity classification is still indexing.
8
Pith papers citing it
fields
cs.CV 8years
2026 8verdicts
UNVERDICTED 8representative citing papers
LatentHDR generates structurally consistent panoramic HDR images by producing one scene latent with a diffusion backbone then deterministically mapping it to multiple exposure latents via a lightweight conditional head.
ExpoCM enables fast one-step single-image HDR reconstruction via exposure-dependent perturbations and region-conditioned consistency trajectories derived from a probability flow ODE.
An exposure-decoupled modulo formulation and iteration-free diffusion-prior unwrapping enable 1000 FPS full-color HDR imaging on spike cameras while cutting bandwidth from 20 Gbps to 6 Gbps.
LumaFlux is a physically and perceptually guided diffusion transformer for SDR-to-HDR conversion that introduces PGA, PCM, and HDR Residual Coupler modules plus a new training corpus and benchmark, outperforming prior ITM methods.
HDR video generation is achieved by logarithmically encoding HDR imagery to align with pretrained generative model latents, enabling minimal fine-tuning and degradation-based inference of missing content.
DiffHDR converts LDR videos to HDR by formulating the task as generative radiance inpainting in a video diffusion model's latent space, using Log-Gamma encoding and synthesized training data to achieve better fidelity and stability than prior methods.
FDIM is a new hybrid feature-distance video quality metric trained on over 16k sequences that shows strong generalization and correlation with human judgments across ten unseen SDR/HDR datasets and diverse codecs.
citing papers explorer
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Single-Shot HDR Recovery via a Video Diffusion Prior
Single-shot HDR is achieved by conditioning a video diffusion model on an LDR input to generate an exposure bracket and fusing the bracket with per-pixel weights from a lightweight UNet.
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LatentHDR: Decoupling Exposure from Diffusion via Conditional Latent-to-Latent Mapping for Text/Image-to-Panoramic HDR
LatentHDR generates structurally consistent panoramic HDR images by producing one scene latent with a diffusion backbone then deterministically mapping it to multiple exposure latents via a lightweight conditional head.
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ExpoCM: Exposure-Aware One-Step Generative Single-Image HDR Reconstruction
ExpoCM enables fast one-step single-image HDR reconstruction via exposure-dependent perturbations and region-conditioned consistency trajectories derived from a probability flow ODE.
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High-Speed Full-Color HDR Imaging via Unwrapping Modulo-Encoded Spike Streams
An exposure-decoupled modulo formulation and iteration-free diffusion-prior unwrapping enable 1000 FPS full-color HDR imaging on spike cameras while cutting bandwidth from 20 Gbps to 6 Gbps.
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LumaFlux: Lifting 8-Bit Worlds to HDR Reality with Physically-Guided Diffusion Transformers
LumaFlux is a physically and perceptually guided diffusion transformer for SDR-to-HDR conversion that introduces PGA, PCM, and HDR Residual Coupler modules plus a new training corpus and benchmark, outperforming prior ITM methods.
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HDR Video Generation via Latent Alignment with Logarithmic Encoding
HDR video generation is achieved by logarithmically encoding HDR imagery to align with pretrained generative model latents, enabling minimal fine-tuning and degradation-based inference of missing content.
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DiffHDR: Re-Exposing LDR Videos with Video Diffusion Models
DiffHDR converts LDR videos to HDR by formulating the task as generative radiance inpainting in a video diffusion model's latent space, using Log-Gamma encoding and synthesized training data to achieve better fidelity and stability than prior methods.
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FDIM: A Feature-distance-based Generic Video Quality Metric for Versatile Codecs
FDIM is a new hybrid feature-distance video quality metric trained on over 16k sequences that shows strong generalization and correlation with human judgments across ten unseen SDR/HDR datasets and diverse codecs.