Jointly Optimizing Color Rendition and In-Camera Backgrounds in an RGB Virtual Production Stage

• URL: http://arxiv.org/abs/2205.12403v1
• Date: Tue, 24 May 2022 23:23:40 GMT
• Title: Jointly Optimizing Color Rendition and In-Camera Backgrounds in an RGB Virtual Production Stage
• Abstract summary: LED panels used in virtual production systems produce problematic color shifts when used as lighting due to their peaky spectral output from narrow-band red, green, and blue LEDs. We present an improved color calibration process for virtual production stages which ameliorates this color rendition problem while also passing through accurate in-camera background colors.
• Score: 2.2304863069891834
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: While the LED panels used in virtual production systems can display vibrant imagery with a wide color gamut, they produce problematic color shifts when used as lighting due to their peaky spectral output from narrow-band red, green, and blue LEDs. In this work, we present an improved color calibration process for virtual production stages which ameliorates this color rendition problem while also passing through accurate in-camera background colors. We do this by optimizing linear color correction transformations for 1) the LED panel pixels visible in the field of view of the camera, 2) the pixels outside the field of view of the camera illuminating the subjects, and, as a post-process, 3) the pixel values recorded by the camera. The result is that footage shot in an RGB LED panel virtual production stage can exhibit more accurate skin tones and costume colors while still reproducing the desired colors of the in-camera background.

Related papers

• CameraAnything: Refilming Videos with Arbitrary Camera Control [104.67227614978822]
  We introduce CameraAnything, the first unified framework for camera controlled video editing.<n>It enables joint control of both intrinsic and extrinsic camera parameters.<n>With a tailored training strategy, CameraAnything enables expressive video reshooting with arbitrary viewpoint control, focal length adjustment, resolution adaptation, and multi-shot transitions within a single generation process.
  arXiv  Detail & Related papers  (2026-07-27T15:55:08Z)
• Color Pass-Through via Camera-Display Coupling [17.070341956620176]
  We propose Color Pass-Through, an end-to-end learned framework that operates directly on captured images.<n> Coupling the camera and display yields two practical advantages.<n>Our method achieves an average gain of +2.0 points on a 5-point user study and more than 2x improvement on quantitative metrics.
  arXiv  Detail & Related papers  (2026-07-14T13:16:10Z)
• Illuminant-Adaptive 3D Lookup Tables for Camera Color Correction [10.971431168902166]
  We propose a color correction framework based on illuminant-adaptive three-dimensional lookup tables (LUTs)<n>Our method combines a chromaticity-aware illuminant representation with a non-linear color transformation, enabling accurate correction under illuminants.<n> Experiments across multiple cameras, illuminants, reflectance datasets, and real captured images demonstrate consistent improvements over existing methods for color correction.
  arXiv  Detail & Related papers  (2026-07-13T15:19:35Z)
• VIRGi: View-dependent Instant Recoloring of 3D Gaussians Splats [53.602701067430075]
  We introduce VIRGi, a novel approach for rapidly editing the color of scenes modeled by 3DGS.<n>By fine-tuning the weights of a single user, the color edits are seamlessly propagated to the entire scene in just two seconds.<n>An exhaustive validation on diverse datasets demonstrates significant quantitative and qualitative advancements over competitors.
  arXiv  Detail & Related papers  (2026-03-03T13:41:17Z)
• Unifying Color and Lightness Correction with View-Adaptive Curve Adjustment for Robust 3D Novel View Synthesis [73.27997579020233]
  We propose Luminance-GS++, a 3DGS-based framework for robust NVS under diverse illumination conditions.<n>Our method combines a globally view-adaptive lightness adjustment with a local pixel-wise residual refinement for precise color correction.
  arXiv  Detail & Related papers  (2026-02-20T16:20:50Z)
• V-RGBX: Video Editing with Accurate Controls over Intrinsic Properties [31.579053991884845]
  We present V-RGBX, the first end-to-end framework for editable video editing.<n>V-RGBX unifies three key capabilities: video inverse rendering into intrinsic channels, video synthesis from these intrinsic representations, and editable-based video editing conditioned on intrinsic channels.<n>We show that V-RGBX produces temporally consistent, photorealistic videos while propagating intrinsic appearance edits across sequences in a physically plausible manner.
  arXiv  Detail & Related papers  (2025-12-12T18:59:54Z)
• Perception-Inspired Color Space Design for Photo White Balance Editing [20.114221919949603]
  White balance (WB) is a key step in the image signal processor (ISP) pipeline.<n>We propose a novel framework for WB correction that leverages a perception-inspired Learnable HSI (LHSI) color space.
  arXiv  Detail & Related papers  (2025-12-10T07:27:16Z)
• Off the Planckian Locus: Using 2D Chromaticity to Improve In-Camera Color [14.28369643988171]
  Traditional in-camera colorimetric mapping relies on correlated color temperature (CCT)-based transforms optimized for Planckian illuminants such as CIE A and D65.<n>Modern lighting technologies can deviate substantially from the Planckian locus, exposing the limitations of relying on conventional one-dimensional CCT for illumination characterization.<n>We replace conventional CCT with a lightweight multi-layer perceptron (MLP) that accommodates 2D chromaticity features for robust colorimetric mapping under non-Planckian illuminants.
  arXiv  Detail & Related papers  (2025-11-21T10:49:04Z)
• Color3D: Controllable and Consistent 3D Colorization with Personalized Colorizer [58.94607850223466]
  We present Color3D, a highly adaptable framework for colorizing both static and dynamic 3D scenes from monochromatic inputs.<n>Our approach is able to preserve color diversity and steerability while ensuring cross-view and cross-time consistency.
  arXiv  Detail & Related papers  (2025-10-11T10:21:19Z)
• Dark-EvGS: Event Camera as an Eye for Radiance Field in the Dark [51.68144172958247]
  We propose Dark-EvGS, the first event-assisted 3D GS framework that enables the reconstruction of bright frames from arbitrary viewpoints.<n>Our method achieves better results than existing methods, conquering radiance field reconstruction under challenging low-light conditions.
  arXiv  Detail & Related papers  (2025-07-16T05:54:33Z)
• Learning Physics-Informed Color-Aware Transforms for Low-Light Image Enhancement [5.8550460201927725]
  We introduce a novel approach to low-light image enhancement based on decomposed physics-informed priors. Existing methods that directly map low-light to normal-light images in the sRGB color space suffer from inconsistent color predictions. Our proposed PiCat framework demonstrates superior performance compared to state-of-the-art methods across five benchmark datasets.
  arXiv  Detail & Related papers  (2025-04-16T09:23:38Z)
• Discovering an Image-Adaptive Coordinate System for Photography Processing [51.164345878060956]
  We propose a novel algorithm, IAC, to learn an image-adaptive coordinate system in the RGB color space before performing curve operations. This end-to-end trainable approach enables us to efficiently adjust images with a jointly learned image-adaptive coordinate system and curves.
  arXiv  Detail & Related papers  (2025-01-11T06:20:07Z)
• In-Pixel Foreground and Contrast Enhancement Circuits with Customizable Mapping [0.4999814847776097]
  In-pixel contrast enhancement circuit performs image processing directly within the pixel circuit. In foreground enhancement mode, it suppresses low-intensity background pixels to nearly zero. In contrast enhancement mode, it improves overall image contrast.
  arXiv  Detail & Related papers  (2024-10-23T17:26:22Z)
• ThermalNeRF: Thermal Radiance Fields [32.881758519242155]
  We propose a unified framework for scene reconstruction from a set of LWIR and RGB images. We calibrate the RGB and infrared cameras with respect to each other, as a preprocessing step. We show that our method is capable of thermal super-resolution, as well as visually removing obstacles to reveal objects occluded in either the RGB or thermal channels.
  arXiv  Detail & Related papers  (2024-07-22T02:51:29Z)
• Colorizing Monochromatic Radiance Fields [55.695149357101755]
  We consider reproducing color from monochromatic radiance fields as a representation-prediction task in the Lab color space. By first constructing the luminance and density representation using monochromatic images, our prediction stage can recreate color representation on the basis of an image colorization module. We then reproduce a colorful implicit model through the representation of luminance, density, and color.
  arXiv  Detail & Related papers  (2024-02-19T14:47:23Z)
• Learning Naturally Aggregated Appearance for Efficient 3D Editing [94.47518916521065]
  We propose to replace the color field with an explicit 2D appearance aggregation, also called canonical image. To avoid the distortion effect and facilitate convenient editing, we complement the canonical image with a projection field that maps 3D points onto 2D pixels for texture lookup. Our representation, dubbed AGAP, well supports various ways of 3D editing (e.g., stylization, interactive drawing, and content extraction) with no need of re-optimization.
  arXiv  Detail & Related papers  (2023-12-11T18:59:31Z)
• GPU Accelerated Color Correction and Frame Warping for Real-time Video Stitching [11.145471040390268]
  Traditional image stitching focuses on a single panorama frame without considering the spatial-temporal consistency in videos. In this paper, we propose a real-time system to stitch multiple video sequences into panoramic video sequences.
  arXiv  Detail & Related papers  (2023-08-17T23:28:39Z)
• Colour alignment for relative colour constancy via non-standard references [11.92389176996629]
  Relative colour constancy is an essential requirement for many scientific imaging applications. We propose a colour alignment model that considers the camera image formation as a black-box. It formulates colour alignment as a three-step process: camera response calibration, response linearisation, and colour matching.
  arXiv  Detail & Related papers  (2021-12-30T15:58:55Z)
• Image color correction, enhancement, and editing [14.453616946103132]
  We study the color correction problem from the standpoint of the camera's image signal processor (ISP) In particular, we propose auto image recapture methods to generate different realistic versions of the same camera-rendered image with new colors.
  arXiv  Detail & Related papers  (2021-07-28T01:14:12Z)
• Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from RGB [84.1657998542458]
  It has been proven that the reconstruction accuracy relies heavily on the spectral response of the RGB camera in use. This paper explores the filter-array based color imaging mechanism of existing RGB cameras, and proposes to design the IR-cut filter properly for improved spectral recovery.
  arXiv  Detail & Related papers  (2021-03-26T19:42:21Z)
• Sampling Based Scene-Space Video Processing [89.49726406622842]
  We present a novel, sampling-based framework for processing video. It enables high-quality scene-space video effects in the presence of inevitable errors in depth and camera pose estimation. We present results for various casually captured, hand-held, moving, compressed, monocular videos.
  arXiv  Detail & Related papers  (2021-02-05T05:55:04Z)
• Scene relighting with illumination estimation in the latent space on an encoder-decoder scheme [68.8204255655161]
  In this report we present methods that we tried to achieve that goal. Our models are trained on a rendered dataset of artificial locations with varied scene content, light source location and color temperature. With this dataset, we used a network with illumination estimation component aiming to infer and replace light conditions in the latent space representation of the concerned scenes.
  arXiv  Detail & Related papers  (2020-06-03T15:25:11Z)
• 3D Photography using Context-aware Layered Depth Inpainting [50.66235795163143]
  We propose a method for converting a single RGB-D input image into a 3D photo. A learning-based inpainting model synthesizes new local color-and-depth content into the occluded region. The resulting 3D photos can be efficiently rendered with motion parallax.
  arXiv  Detail & Related papers  (2020-04-09T17:59:06Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.