ACM Transactions on Graphics
ISSN / EISSN : 0730-0301 / 1557-7368
Published by: Association for Computing Machinery (ACM) (10.1145)
Total articles ≅ 4,746
Latest articles in this journal
Published: 21 June 2022
ACM Transactions on Graphics; https://doi.org/10.1145/3544777
Recently, numerous facial editing techniques have been proposed that leverage the generative power of a pretrained StyleGAN. To successfully edit an image this way, one must first project (or invert) the image into the pretrained generator’s domain. As it turns out, StyleGAN’s latent space induces an inherent tradeoff between distortion and editability, i.e., between maintaining the original appearance and convincingly altering its attributes. Hence, it remains challenging to apply ID-preserving edits to real facial images. In this paper, we present an approach to bridge this gap. The idea is pivotal tuning — a brief training process that preserves editing quality, while surgically changing the portrayed identity and appearance. In Pivotal Tuning Inversion (PTI), an initial inverted latent code serves as a pivot, around which the generator is fine-tuned. At the same time, a regularisation term keeps nearby identities intact, to locally contain the effect. We further show that pivotal tuning also applies to accommodating for a multitude of faces, while introducing negligible distortion on the rest of the domain. We validate our technique through inversion and editing metrics, and show preferable scores to state-of-the-art methods. Lastly, we present successful editing for harder cases, including elaborate make-up or headwear
Published: 21 June 2022
ACM Transactions on Graphics; https://doi.org/10.1145/3544778
This paper proposes a method for computing the visible occluding contours of subdivision surfaces. The paper first introduces new theory for contour visibility of smooth surfaces. Necessary and sufficient conditions are introduced for when a sampled occluding contour is valid, that is, when it may be assigned consistent visibility. Previous methods do not guarantee these conditions, which helps explain why smooth contour visibility has been such a challenging problem in the past. The paper then proposes an algorithm that, given a subdivision surface, finds sampled contours satisfying these conditions, and then generates a new triangle mesh matching the given occluding contours. The contours of the output triangle mesh may then be rendered with standard non-photorealistic rendering algorithms, using the mesh for visibility computation. The method can be applied to any triangle mesh, by treating it as the base mesh of a subdivision surface.
ACM Transactions on Graphics; https://doi.org/10.1145/3522671
Depth sensors have emerged as a cornerstone sensor modality with diverse applications in personal hand-held devices, robotics, scientific imaging, autonomous vehicles, and more. In particular, correlation Time-of-Flight (ToF) sensors have found widespread adoption for meter-scale indoor applications such as object tracking and pose estimation. While they offer high depth resolution at competitive costs, the precision of these indirect ToF sensors is fundamentally limited by their modulation contrast, which is in turn limited by the effects of photo-conversion noise. In contrast, optical interferometric methods can leverage short illumination modulation wavelengths to achieve depth precision three orders of magnitude greater than ToF, but typically find their range restricted to the sub-centimeter. In this work, we merge concepts from both correlation ToF design and interferometric imaging; a step towards bridging the gap between these methods. We propose a computational ToF imaging method which optically computes the GHz ToF correlation signal in free space before photo-conversion. To acquire a depth map, we scan a scene point-wise and computationally unwrap the collected correlation measurements. Specifically, we repurpose electro-optical modulators used in optical communication for ToF imaging with centimeter-wave signals, and achieve all-optical correlation at 7.15 and 14.32 GHz modulation frequencies. While GHz modulation frequencies increase depth precision, these high modulation rates also pose a technical challenge. They result in dozens of wraps per meter which cannot be estimated robustly by existing phase unwrapping methods. We tackle this problem with a proposed segmentation-inspired phase unwrapping network , which exploits the correlation of adjacent GHz phase measurements to classify regions into their respective wrap counts. We validate this method in simulation and experimentally, and demonstrate precise depth sensing using centimeter wave modulation that is robust to surface texture and ambient light. Compared to existing analog demodulation methods, the proposed system outperforms all of them across all tested scenarios.
ACM Transactions on Graphics; https://doi.org/10.1145/3533427
This paper presents a novel sparse non-parametric BRDF model derived using a machine learning approach to represent the space of possible BRDFs using a set of multidimensional sub-spaces, or dictionaries. By training the dictionaries under a sparsity constraint, the model guarantees high quality representations with minimal storage requirements and an inherent clustering of the BDRF-space. The model can be trained once and then reused to represent a wide variety of measured BRDFs. Moreover, the proposed method is flexible to incorporate new unobserved data sets, parameterizations, and transformations. In addition, we show that any two, or more, BRDFs can be smoothly interpolated in the coefficient space of the model rather than the significantly higher-dimensional BRDF space. The proposed sparse BRDF model is evaluated using the MERL, DTU and RGL-EPFL BRDF databases. Experimental results show that the proposed approach results in about 9.75dB higher SNR on average for rendered images as compared to current state-of-the-art models.
ACM Transactions on Graphics; https://doi.org/10.1145/3533426
Non-invasive inspection and imaging techniques are used to acquire non-visible information embedded in samples. Typical applications include medical imaging, defect evaluation, and electronics testing. However, existing methods have specific limitations, including safety risks ( e.g. , X-ray), equipment costs ( e.g. , optical tomography), personnel training ( e.g. , ultrasonography) and material constraints ( e.g. , terahertz spectroscopy). Such constraints make these approaches impractical for everyday scenarios. In this paper, we present a method that is low-cost and practical for non-invasive inspection in everyday settings. Our prototype incorporates a miniaturized near-infrared spectroscopy scanner driven by a computer-controlled 2D-plotter. Our work presents a method to optimize content embedding, as well as a wavelength selection algorithm to extract content without human supervision. We show that our method can successfully extract occluded text through a paper stack of up to 16 pages. In addition, we present a deep-learning based image enhancement model that can further improve the image quality and simultaneously decompose overlapping content. Finally, we demonstrate how our method can be generalized to different inks and other layered materials beyond paper. Our approach enables a wide range of content embedding applications, including chipless information embedding, physical secret sharing, 3D print evaluations, and steganography.
ACM Transactions on Graphics; https://doi.org/10.1145/3533768
The task of explicit surface reconstruction is to generate a surface mesh by interpolating a given point cloud. Explicit surface reconstruction is necessary when the point cloud is required to appear exactly on the surface. However, for a non-perfect input, e.g. lack of normals, low density, irregular distribution, thin and tiny parts, high genus, etc, a robust explicit reconstruction method that can generate a high-quality manifold triangulation is missing. We propose a robust explicit surface reconstruction method that starts from an initial simple surface mesh, alternately performs a Filmsticking step and a Sculpting step of the initial mesh and converges when the surface mesh interpolates all input points (except outliers) and remains stable. The Filmsticking is to minimize the geometric distance between the surface mesh and the point cloud through iteratively performing a restricted Voronoi diagram technique on the surface mesh, while the Sculpting is to bootstrap the Filmsticking iteration from local minima by applying appropriate geometric and topological changes of the surface mesh. Our algorithm is fully automatic and produces high-quality surface meshes for non-perfect inputs that are typically considered to be challenging for prior state-of-the-art. We conducted extensive experiments on simulated scans and real scans to validate the effectiveness of our approach.
Published: 30 April 2022
ACM Transactions on Graphics, Volume 41, pp 1-17; https://doi.org/10.1145/3503460
In art, hatching means drawing patterns of roughly parallel lines. Even with skill and time, an artist can find these patterns difficult to create and edit. Our new artistic primitive—the hatching shape—facilitates hatching for an artist drawing from imagination. A hatching shape comprises a mask and three fields: width, spacing, and direction. Streamline advection uses these fields to create hatching marks. A hatching shape also contains barrier curves: deliberate discontinuities useful for drawing complex forms. We explain several operations on hatching shapes, such as the multi-dir operation, an easy way to depict 3D form using a hatching shape’s direction field. We also explain the modifications to streamline advection necessary to produce hatching marks from a hatching shape.
Published: 30 April 2022
ACM Transactions on Graphics, Volume 41, pp 1-21; https://doi.org/10.1145/3490168
We present a novel, fast differentiable simulator for soft-body learning and control applications. Existing differentiable soft-body simulators can be classified into two categories based on their time integration methods: Simulators using explicit timestepping schemes require tiny timesteps to avoid numerical instabilities in gradient computation, and simulators using implicit time integration typically compute gradients by employing the adjoint method and solving the expensive linearized dynamics. Inspired by Projective Dynamics ( PD ), we present Differentiable Projective Dynamics ( DiffPD ), an efficient differentiable soft-body simulator based on PD with implicit time integration. The key idea in DiffPD is to speed up backpropagation by exploiting the prefactorized Cholesky decomposition in forward PD simulation. In terms of contact handling, DiffPD supports two types of contacts: a penalty-based model describing contact and friction forces and a complementarity-based model enforcing non-penetration conditions and static friction. We evaluate the performance of DiffPD and observe it is 4–19 times faster compared with the standard Newton’s method in various applications including system identification, inverse design problems, trajectory optimization, and closed-loop control. We also apply DiffPD in a reality-to-simulation ( real-to-sim ) example with contact and collisions and show its capability of reconstructing a digital twin of real-world scenes.
Published: 30 April 2022
ACM Transactions on Graphics, Volume 41, pp 1-16; https://doi.org/10.1145/3488006
We present an interactive design system for knitting that allows users to create template patterns that can be fabricated using an industrial knitting machine. Our interactive design tool is novel in that it allows direct control of key knitting design axes we have identified in our formative study and does so consistently across the variations of an input parametric template geometry. This is achieved with two key technical advances. First, we present an interactive meshing tool that lets users build a coarse quadrilateral mesh that adheres to their knit design guidelines. This solution ensures consistency across the parameter space for further customization over shape variations and avoids helices, promoting knittability. Second, we lift and formalize low-level machine knitting constraints to the level of this coarse quad mesh. This enables us to not only guarantee hand- and machine-knittability, but also provides automatic design assistance through auto-completion and suggestions. We show the capabilities through a set of fabricated examples that illustrate the effectiveness of our approach in creating a wide variety of objects and interactively exploring the space of design variations.
Published: 30 April 2022
ACM Transactions on Graphics, Volume 41, pp 1-17; https://doi.org/10.1145/3487909
Tangles are complex patterns, which are often used to decorate the surface of real-world artisanal objects. They consist of arrangements of simple shapes organized into nested hierarchies, obtained by recursively splitting regions to add progressively finer details. In this article, we show that 3D digital shapes can be decorated with tangles by working interactively in the intrinsic metric of the surface. Our tangles are generated by the recursive application of only four operators, which are derived from tracing the isolines or the integral curves of geodesics fields generated from selected seeds on the surface. Based on this formulation, we present an interactive application that lets designers model complex recursive patterns directly on the object surface without relying on parametrization. We reach interactive speed on meshes of a few million triangles by relying on an efficient approximate graph-based geodesic solver.