Zobrazeno 1 - 10
of 405
pro vyhledávání: '"Chen Yongwei"'
Autoregressive models have demonstrated remarkable success across various fields, from large language models (LLMs) to large multimodal models (LMMs) and 2D content generation, moving closer to artificial general intelligence (AGI). Despite these adv
Externí odkaz:
http://arxiv.org/abs/2411.16856
Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing explicit spati
Externí odkaz:
http://arxiv.org/abs/2410.16272
Generating high-quality 3D assets from a given image is highly desirable in various applications such as AR/VR. Recent advances in single-image 3D generation explore feed-forward models that learn to infer the 3D model of an object without optimizati
Externí odkaz:
http://arxiv.org/abs/2403.12409
Automatic 3D content creation has achieved rapid progress recently due to the availability of pre-trained, large language models and image diffusion models, forming the emerging topic of text-to-3D content creation. Existing text-to-3D methods common
Externí odkaz:
http://arxiv.org/abs/2303.13873
Creation of 3D content by stylization is a promising yet challenging problem in computer vision and graphics research. In this work, we focus on stylizing photorealistic appearance renderings of a given surface mesh of arbitrary topology. Motivated b
Externí odkaz:
http://arxiv.org/abs/2210.11277
Deep-learning-based approaches for retinal lesion segmentation often require an abundant amount of precise pixel-wise annotated data. However, coarse annotations such as circles or ellipses for outlining the lesion area can be six times more efficien
Externí odkaz:
http://arxiv.org/abs/2208.14294
Masked auto-encoding is a popular and effective self-supervised learning approach to point cloud learning. However, most of the existing methods reconstruct only the masked points and overlook the local geometry information, which is also important t
Externí odkaz:
http://arxiv.org/abs/2207.03111
Publikováno v:
In Construction and Building Materials 20 December 2024 456
Publikováno v:
In Vacuum January 2025 231 Part A
Semantic analyses of object point clouds are largely driven by releasing of benchmarking datasets, including synthetic ones whose instances are sampled from object CAD models. However, learning from synthetic data may not generalize to practical scen
Externí odkaz:
http://arxiv.org/abs/2203.03833