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Robust Pose Transfer with Dynamic Details using Neural Video Rendering
[article]
2021
arXiv
pre-print
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Through extensive comparisons, we demonstrate that our neural human video renderer is capable of achieving both clearer dynamic details and more robust performance even on accessible short videos with ...
Pose transfer of human videos aims to generate a high fidelity video of a target person imitating actions of a source person. ...
Here, we summarize the technical contributions as follows: • A novel end-to-end neural rendering framework for human video generation with dynamic details using accessible monocular video as training data ...
arXiv:2106.14132v2
fatcat:dslhnmaborfstasn2qh6lwejly
Video-driven Neural Physically-based Facial Asset for Production
[article]
2022
arXiv
pre-print
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2022 pre-print arXiv:2202.05592v1 fatcat:pgb4btd7rnfo7d6ucj5tdypxeyOther Versions
In addition, our neural asset along with fast adaptation schemes can also be deployed to handle in-the-wild videos. ...
In this paper, we present a new learning-based, video-driven approach for generating dynamic facial geometries with high-quality physically-based assets. ...
Our method achieves detailed video-driven results from different identities with dynamic textures, which leads to photo-realistic rendering.
Fig. 17 . 17 Fig. 17. ...
arXiv:2202.05592v3
fatcat:tfbmwzburfh7hicvdgwzd4erga
Neural Human Video Rendering by Learning Dynamic Textures and Rendering-to-Video Translation
[article]
2021
arXiv
pre-print
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Synthesizing realistic videos of humans using neural networks has been a popular alternative to the conventional graphics-based rendering pipeline due to its high efficiency. ...
Given the pose information, the first CNN predicts a dynamic texture map that contains time-coherent high-frequency details, and the second CNN conditions the generation of the final video on the temporally ...
These benefits come from a well-designed three-stage pipeline that first generates a dynamic texture with time-coherent high-frequency details and then renders the mesh with the dynamic texture, which ...
arXiv:2001.04947v3
fatcat:ppii2ilexze7nkejshrohlky4u
A New Dimension in Testimony: Relighting Video with Reflectance Field Exemplars
[article]
2021
arXiv
pre-print
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We also use a differentiable renderer to provide feedback for the network by matching the relit images with the input video frames. ...
This semi-supervised training scheme allows the neural network to handle unseen poses in the dataset as well as compensate for the lighting estimation error. ...
But instead of recording OLAT's for every moment of the video, our neural network infers OLATs for each video frame based on exemplars from static poses, enabling dynamic performance relighting. ...
arXiv:2104.02773v1
fatcat:4pynaycd5rb4zgkbt3i4sq357q
Animatable Neural Radiance Fields from Monocular RGB Videos
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2106.13629v1 fatcat:rruluon2gncwdm526vixbqwcr4
We present animatable neural radiance fields (animatable NeRF) for detailed human avatar creation from monocular videos. ...
Our approach extends neural radiance fields (NeRF) to the dynamic scenes with human movements via introducing explicit pose-guided deformation while learning the scene representation network. ...
We can use the volumetric rendering (Section 3.3) to render our neural radiance field. ...
arXiv:2106.13629v2
fatcat:tg3f5jyyhbbcjhpisay5pe6b5e
Head2Head: Video-based Neural Head Synthesis
[article]
2020
arXiv
pre-print
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We demonstrate that the proposed method can transfer facial expressions, pose and gaze of a source actor to a target video in a photo-realistic fashion more accurately than state-of-the-art methods. ...
In particular, contrary to the model-based approaches or recent frame-based methods that use Deep Convolutional Neural Networks (DCNNs) to generate individual frames, we propose a novel method that (a) ...
In this method, texture features are learned from the target video and translated to RGB images with a neural renderer. ...
arXiv:2005.10954v1
fatcat:kw43v65lindf3oapvw7rnjxgbu
Neural Re-Rendering of Humans from a Single Image
[article]
2021
arXiv
pre-print
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The body model with the rendered feature maps is fed through a neural image-translation network that creates the final rendered colour image. ...
To address these challenges, we propose a new method for neural re-rendering of a human under a novel user-defined pose and viewpoint, given one input image. ...
Neural Re-Rendering of Humans from a Single Image ...
arXiv:2101.04104v1
fatcat:6snujhlbpbgd7nc4gcw62soivy
Real-Time Neural Character Rendering with Pose-Guided Multiplane Images
[article]
2022
arXiv
pre-print
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We propose pose-guided multiplane image (MPI) synthesis which can render an animatable character in real scenes with photorealistic quality. ...
Our method generalizes the image-to-image translation paradigm, which translates the human pose to a 3D scene representation -- MPIs that can be rendered in free viewpoints, using the multi-views captures ...
Neural scene representation Instead of rendering with a black-box image translation process, recent works turn to using neural networks to model some intrinsic aspects of the scene followed by a physics-based ...
arXiv:2204.11820v1
fatcat:svrgg7sr2vgdfpua74rgo6cqge
Artemis: Articulated Neural Pets with Appearance and Motion synthesis
[article]
2022
arXiv
pre-print
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In this paper, we present ARTEMIS, a novel neural modeling and rendering pipeline for generating ARTiculated neural pets with appEarance and Motion synthesIS. ...
Finally, we propose a novel shading network to generate high-fidelity details of appearance and opacity under novel poses from appearance and density feature maps. ...
Besides, we thank Zhenxiao Yu from Shang-haiTech University for producing a supplementary video. ...
arXiv:2202.05628v2
fatcat:v7f6tg64fvfohmtl7riiecn5fu
ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on
[article]
2021
arXiv
pre-print
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Virtual try-on has garnered interest as a neural rendering benchmark task to evaluate complex object transfer and scene composition. ...
Specifically, we investigate the effect of different pose annotations, self-attention layer placement, and activation functions on the quantitative and qualitative performance of video virtual try-on. ...
detail, exhibit smooth temporal dynamics, establish temporal consistency, and blend well with the scene's lighting. ...
arXiv:2012.10495v2
fatcat:agqqtz4xercwld4ou7ed4ksfdy
Layered Neural Rendering for Retiming People in Video
[article]
2021
arXiv
pre-print
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The layers can be individually retimed and recombined into a new video, allowing us to achieve realistic, high-quality renderings of retiming effects for real-world videos depicting complex actions and ...
A key property of our model is that it not only disentangles the direct motions of each person in the input video, but also correlates each person automatically with the scene changes they generate -- ...
ACKNOWLEDGMENTS We thank the friends and family that appeared in our videos. The original Ballroom video belongs to Desert Classic Dance. ...
arXiv:2009.07833v2
fatcat:zgg5nx6ykrhmzjta5a27rpvvgy
Everybody's Talkin': Let Me Talk as You Want
[article]
2020
arXiv
pre-print
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Finally, we introduce a novel video rendering network and a dynamic programming method to construct a temporally coherent and photo-realistic video. ...
The audio-translated expression parameters are then used to synthesize a photo-realistic human subject in each video frame, with the movement of the mouth regions precisely mapped to the source audio. ...
Tongue: In our method, our Neural Video Rendering Network produces lip fiducials and the teeth proxy adds the teeth high-frequency details. ...
arXiv:2001.05201v1
fatcat:wes6abhwinghfohufyh46dacwy
Human View Synthesis using a Single Sparse RGB-D Input
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2112.13889v1 fatcat:kg3j6ohhcbgmribnisivg3v2oy
We propose an architecture to learn dense features in novel views obtained by sphere-based neural rendering, and create complete renders using a global context inpainting model. ...
Additionally, an enhancer network leverages the overall fidelity, even in occluded areas from the original view, producing crisp renders with fine details. ...
Instead, we use the dynamic per-
a dynamic Neural Radiance Field. ...
arXiv:2112.13889v2
fatcat:u6e2uuinxra2lnrknjmrcsd6yq
HVTR: Hybrid Volumetric-Textural Rendering for Human Avatars
[article]
2021
arXiv
pre-print
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While this allows us to represent 3D geometry with changing topology, volumetric rendering is computationally heavy. ...
Hence we employ only a rough volumetric representation using a pose-conditioned downsampled neural radiance field (PD-NeRF), which we can render efficiently at low resolutions. ...
Neural rendering and reenactment of Dense pose transfer. European Conference on Computer Vi-
human actor videos. ...
arXiv:2112.10203v1
fatcat:fypyninknbfopb73m343dmeoua
Head2Head++: Deep Facial Attributes Re-Targeting
[article]
2020
arXiv
pre-print
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We manage to capture the complex non-rigid facial motion from the driving monocular performances and synthesise temporally consistent videos, with the aid of a sequential Generator and an ad-hoc Dynamics ...
Our method is different to purely 3D model-based approaches, or recent image-based methods that use Deep Convolutional Neural Networks (DCNNs) to generate individual frames. ...
, neural renderer. ...
arXiv:2006.10199v1
fatcat:ylapnwbkzjes5gejb4zmnou6ym
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