Results 11 to 20 of about 218,039 (317)
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs [PDF]
International Conference on Learning Representations, 2022 The formalization of existing mathematical proofs is a notoriously difficult process. Despite decades of research on automation and proof assistants, writing formal proofs remains arduous and only accessible to a few experts.
Albert Qiaochu Jiang +8 more
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Sketch-Guided Text-to-Image Diffusion Models [PDF]
International Conference on Computer Graphics and Interactive Techniques, 2022 Text-to-Image models have introduced a remarkable leap in the evolution of machine learning, demonstrating high-quality synthesis of images from a given text-prompt.
Andrey Voynov, Kfir Aberman, D. Cohen-Or
semanticscholar +1 more source
CLIP for All Things Zero-Shot Sketch-Based Image Retrieval, Fine-Grained or Not [PDF]
Computer Vision and Pattern Recognition, 2023 In this paper, we leverage CLIP for zero-shot sketch based image retrieval (ZS-SBIR). We are largely inspired by recent advances on foundation models and the unparalleled generalisation ability they seem to offer, but for the first time tailor it to ...
Aneeshan Sain +5 more
semanticscholar +1 more source
SkCoder: A Sketch-based Approach for Automatic Code Generation [PDF]
International Conference on Software Engineering, 2023 Recently, deep learning techniques have shown great success in automatic code generation. Inspired by the code reuse, some researchers propose copy-based approaches that can copy the content from similar code snippets to obtain better performance ...
Jia Li +5 more
semanticscholar +1 more source
DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models [PDF]
Neural Information Processing Systems, 2023 We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide vector sketch synthesis.
Ximing Xing +5 more
semanticscholar +1 more source
SECAD-Net: Self-Supervised CAD Reconstruction by Learning Sketch-Extrude Operations [PDF]
Computer Vision and Pattern Recognition, 2023 Reverse engineering CAD models from raw geometry is a classic but strenuous research problem. Previous learning-based methods rely heavily on labels due to the supervised design patterns or reconstruct CAD shapes that are not easily editable.
Pu Li +3 more
semanticscholar +1 more source
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation [PDF]
IEEE International Conference on Computer Vision, 2023 Diffusion probabilistic models have achieved remarkable success in text guided image generation. However, generating 3D shapes is still challenging due to the lack of sufficient data containing 3D models along with their descriptions.
Zijie Wu +4 more
semanticscholar +1 more source
StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval [PDF]
Computer Vision and Pattern Recognition, 2021 Sketch-based image retrieval (SBIR) is a cross-modal matching problem which is typically solved by learning a joint embedding space where the semantic content shared between photo and sketch modalities are preserved.
Aneeshan Sain +4 more
semanticscholar +1 more source
ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsing [PDF]
European Conference on Computer Vision, 2022 Sketch-and-extrude is a common and intuitive modeling process in computer aided design. This paper studies the problem of learning the shape given in the form of point clouds by inverse sketch-and-extrude.
Daxuan Ren +4 more
semanticscholar +1 more source
A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch [PDF]
European Conference on Computer Vision, 2022 We address the problem of retrieving images with both a sketch and a text query. We present TASK-former (Text And SKetch transformer), an end-to-end trainable model for image retrieval using a text description and a sketch as input.
Patsorn Sangkloy +3 more
semanticscholar +1 more source