Human Body Shape Completion with Implicit Shape and Flow Learning

Zhou, Boyao; Meng, Di; Franco, Jean-Sébastien; Boyer, Edmond

doi:10.1109/cvpr52729.2023.01240

Cited by 3 publications

(1 citation statement)

References 57 publications

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“…4DComplete additionally predicts the occluded geometry as well. Trained on D‐FAUST, Zhou et al [ZFB23] use MLPs to decode flow and SDF from 3D feature volumes unprojected from depth frames, which are enhanced by self‐ and cross‐attention between the source and the target frame.…”

Section: State‐of‐the‐art Methodsmentioning

confidence: 99%

Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes

Yunus,

Lenssen,

Niemeyer

et al. 2024

Computer Graphics Forum

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Reconstructing models of the real world, including 3D geometry, appearance, and motion of real scenes, is essential for computer graphics and computer vision. It enables the synthesizing of photorealistic novel views, useful for the movie industry and AR/VR applications. It also facilitates the content creation necessary in computer games and AR/VR by avoiding laborious manual design processes. Further, such models are fundamental for intelligent computing systems that need to interpret real‐world scenes and actions to act and interact safely with the human world. Notably, the world surrounding us is dynamic, and reconstructing models of dynamic, non‐rigidly moving scenes is a severely underconstrained and challenging problem. This state‐of‐the‐art report (STAR) offers the reader a comprehensive summary of state‐of‐the‐art techniques with monocular and multi‐view inputs such as data from RGB and RGB‐D sensors, among others, conveying an understanding of different approaches, their potential applications, and promising further research directions. The report covers 3D reconstruction of general non‐rigid scenes and further addresses the techniques for scene decomposition, editing and controlling, and generalizable and generative modeling. More specifically, we first review the common and fundamental concepts necessary to understand and navigate the field and then discuss the state‐of‐the‐art techniques by reviewing recent approaches that use traditional and machine‐learning‐based neural representations, including a discussion on the newly enabled applications. The STAR is concluded with a discussion of the remaining limitations and open challenges.

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Section: State‐of‐the‐art Methodsmentioning

confidence: 99%

Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes

Yunus,

Lenssen,

Niemeyer

et al. 2024

Computer Graphics Forum

View full text Add to dashboard Cite

show abstract

GPS-Gaussian: Generalizable Pixel-Wise 3D Gaussian Splatting for Real-Time Human Novel View Synthesis

Zheng,

Zhou,

Shao

et al. 2024

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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A Survey on Realistic Virtual Human Animations: Definitions, Features and Evaluations

Rekik,

Wuhrer,

Hoyet

et al. 2024

Computer Graphics Forum

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Generating realistic animated virtual humans is a problem that has been extensively studied with many applications in different types of virtual environments. However, the creation process of such realistic animations is challenging, especially because of the number and variety of influencing factors, that should then be identified and evaluated. In this paper, we attempt to provide a clearer understanding of how the multiple factors that have been studied in the literature impact the level of realism of animated virtual humans, by providing a survey of studies assessing their realism. This includes a review of features that have been manipulated to increase the realism of virtual humans, as well as evaluation approaches that have been developed. As the challenges of evaluating animated virtual humans in a way that agrees with human perception are still active research problems, this survey further identifies important open problems and directions for future research.

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Human Body Shape Completion with Implicit Shape and Flow Learning

Abstract: Figure 1. Human shape completions with various methods given 2 depth images. NPMs [31] and our approach provide also motion flows.

Cited by 3 publications

References 57 publications

Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes

Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes

GPS-Gaussian: Generalizable Pixel-Wise 3D Gaussian Splatting for Real-Time Human Novel View Synthesis

A Survey on Realistic Virtual Human Animations: Definitions, Features and Evaluations

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