Zobrazeno 1 - 10
of 1 721
pro vyhledávání: '"Chang, A. X."'
We address the challenge of creating 3D assets for household articulated objects from a single image. Prior work on articulated object creation either requires multi-view multi-state input, or only allows coarse control over the generation process. T
Externí odkaz:
http://arxiv.org/abs/2410.16499
Despite much progress in large 3D datasets there are currently few interactive 3D object datasets, and their scale is limited due to the manual effort required in their construction. We introduce the static to openable (S2O) task which creates intera
Externí odkaz:
http://arxiv.org/abs/2409.18896
Autor:
Meeussen, A. S., Bordiga, G., Chang, A. X., Spoettling, B., Becker, K. P., Mahadevan, L., Bertoldi, K.
Mechanical metamaterials -- structures with unusual properties that emerge from their internal architecture -- that are designed to undergo large deformations typically exploit large internal rotations, and therefore, necessitate the incorporation of
Externí odkaz:
http://arxiv.org/abs/2408.16059
We introduce a new approach for generating realistic 3D models with UV maps through a representation termed "Object Images." This approach encapsulates surface geometry, appearance, and patch structures within a 64x64 pixel image, effectively convert
Externí odkaz:
http://arxiv.org/abs/2408.03178
Despite advances in text-to-3D generation methods, generation of multi-object arrangements remains challenging. Current methods exhibit failures in generating physically plausible arrangements that respect the provided text description. We present Sc
Externí odkaz:
http://arxiv.org/abs/2408.02211
Autor:
Gharaee, Zahra, Lowe, Scott C., Gong, ZeMing, Arias, Pablo Millan, Pellegrino, Nicholas, Wang, Austin T., Haurum, Joakim Bruslund, Zarubiieva, Iuliia, Kari, Lila, Steinke, Dirk, Taylor, Graham W., Fieguth, Paul, Chang, Angel X.
As part of an ongoing worldwide effort to comprehend and monitor insect biodiversity, this paper presents the BIOSCAN-5M Insect dataset to the machine learning community and establish several benchmark tasks. BIOSCAN-5M is a comprehensive dataset con
Externí odkaz:
http://arxiv.org/abs/2406.12723
We introduce Duoduo CLIP, a model for 3D representation learning that learns shape encodings from multi-view images instead of point-clouds. The choice of multi-view images allows us to leverage 2D priors from off-the-shelf CLIP models to facilitate
Externí odkaz:
http://arxiv.org/abs/2406.11579
Autor:
Gong, ZeMing, Wang, Austin T., Haurum, Joakim Bruslund, Lowe, Scott C., Taylor, Graham W., Chang, Angel X.
Measuring biodiversity is crucial for understanding ecosystem health. While prior works have developed machine learning models for the taxonomic classification of photographic images and DNA separately, in this work, we introduce a multimodal approac
Externí odkaz:
http://arxiv.org/abs/2405.17537
Autor:
Ma, Xianzheng, Bhalgat, Yash, Smart, Brandon, Chen, Shuai, Li, Xinghui, Ding, Jian, Gu, Jindong, Chen, Dave Zhenyu, Peng, Songyou, Bian, Jia-Wang, Torr, Philip H, Pollefeys, Marc, Nießner, Matthias, Reid, Ian D, Chang, Angel X., Laina, Iro, Prisacariu, Victor Adrian
As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interacting with physical spaces. This survey provides a comprehensive overvie
Externí odkaz:
http://arxiv.org/abs/2405.10255
Neural fields (NeRF) have emerged as a promising approach for representing continuous 3D scenes. Nevertheless, the lack of semantic encoding in NeRFs poses a significant challenge for scene decomposition. To address this challenge, we present a singl
Externí odkaz:
http://arxiv.org/abs/2405.05010