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ACM Transactions on Graphics is a peer-reviewed journal published by ACM, covering Computer Graphics and Visualization Techniques, 3D Shape Modeling and Analysis, Advanced Vision and Imaging. Over its lifetime it has published 6,622 papers, which have received 546,899 citations.
| Publisher | ACM |
|---|---|
| Reference style | Numbered (ACM) Numbered — [1], [2] in the text [1] Ada Smith, Ben Jones, and Cara Lee. 2023. A representative article title. ACM Transactions on Graphics 12, 3, Article 45 (2023).
Formats any DOI in ACM Transactions on Graphics style. No sign-up. |
| Publishes research in | Computer Graphics and Visualization Techniques 3D Shape Modeling and Analysis Advanced Vision and Imaging Advanced Numerical Analysis Techniques Computational Geometry and Mesh Generation |
| ISSN | 0730-0301 |
| Citation impact (2-yr) | 5.73 |
| h-index | 312 |
| i10-index | 4,670 |
| Top institutions publishing here | Adobe Systems (United States) |
| Journal website | tog.acm.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Point clouds provide a flexible geometric representation suitable for countless applications in computer graphics; they also comprise the raw output of most 3D data acquisition devices. While hand-designed features on point clouds have long been proposed in graphics and vision, however, the recent overwhelming success of convolutional neural networks (CNNs) for image analysis suggests the…
The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently, an approach based on optimization by graph-cut has been developed which successfully combines both types of information.…
Radiance Field methods have recently revolutionized novel-view synthesis of scenes captured with multiple photos or videos. However, achieving high visual quality still requires neural networks that are costly to train and render, while recent faster methods inevitably trade off speed for quality. For unbounded and complete scenes (rather than isolated objects) and 1080p resolution rendering,…
Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate. We reduce this cost with a versatile new input encoding that permits the use of a smaller network without sacrificing quality, thus significantly reducing the number of floating point and memory access operations: a small neural network is augmented…
We present a learned model of human body shape and pose-dependent shape variation that is more accurate than previous models and is compatible with existing graphics pipelines. Our Skinned Multi-Person Linear model (SMPL) is a skinned vertex-based model that accurately represents a wide variety of body shapes in natural human poses. The parameters of the…
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