Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Ritchie, Daniel"'
Programs are an increasingly popular representation for visual data, exposing compact, interpretable structure that supports manipulation. Visual programs are usually written in domain-specific languages (DSLs). Finding "good" programs, that only exp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb1e967c4452302e4eec1c292524bda8
Autor:
Sanghi, Aditya, Fu, Rao, Liu, Vivian, Willis, Karl, Shayani, Hooman, Khasahmadi, Amir Hosein, Sridhar, Srinath, Ritchie, Daniel
Recent works have demonstrated that natural language can be used to generate and edit 3D shapes. However, these methods generate shapes with limited fidelity and diversity. We introduce CLIP-Sculptor, a method to address these constraints by producin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::934c5f04712e2326d57754b699a48b09
http://arxiv.org/abs/2211.01427
http://arxiv.org/abs/2211.01427
We present SHRED, a method for 3D SHape REgion Decomposition. SHRED takes a 3D point cloud as input and uses learned local operations to produce a segmentation that approximates fine-grained part instances. We endow SHRED with three decomposition ope
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86a53960410f15316e5b25b869a96c43
http://arxiv.org/abs/2206.03480
http://arxiv.org/abs/2206.03480
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Inferring programs which generate 2D and 3D shapes is important for reverse engineering, editing, and more. Training models to perform this task is complicated because paired (shape, program) data is not readily available for many domains, making exa
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
We propose the Neurally-Guided Shape Parser (NGSP), a method that learns how to assign fine-grained semantic labels to regions of a 3D shape. NGSP solves this problem via MAP inference, modeling the posterior probability of a label assignment conditi
Autor:
Zhang, Zheng, Xu, Ying, Wang, Yanhao, Yao, Bingsheng, Ritchie, Daniel, Wu, Tongshuang, Yu, Mo, Wang, Dakuo, Li, Toby Jia-Jun
Despite its benefits for children's skill development and parent-child bonding, many parents do not often engage in interactive storytelling by having story-related dialogues with their child due to limited availability or challenges in coming up wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd4d6e80befb66747192688620afb666
We present ShapeCrafter, a neural network for recursive text-conditioned 3D shape generation. Existing methods to generate text-conditioned 3D shapes consume an entire text prompt to generate a 3D shape in a single step. However, humans tend to descr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b07c7e6ec66801163686bb1572dbaca6
Autor:
Xu, Ying, Wang, Dakuo, Yu, Mo, Ritchie, Daniel, Yao, Bingsheng, Wu, Tongshuang, Zhang, Zheng, Li, Toby Jia-Jun, Bradford, Nora, Sun, Branda, Hoang, Tran Bao, Sang, Yisi, Hou, Yufang, Ma, Xiaojuan, Yang, Diyi, Peng, Nanyun, Yu, Zhou, Warschauer, Mark
Question answering (QA) is a fundamental means to facilitate assessment and training of narrative comprehension skills for both machines and young children, yet there is scarcity of high-quality QA datasets carefully designed to serve this purpose. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::539516a8a87a171b7f62585ad8d1976a
Manipulating an articulated object requires perceiving itskinematic hierarchy: its parts, how each can move, and howthose motions are coupled. Previous work has explored per-ception for kinematics, but none infers a complete kinematichierarchy on nev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2e292f7a68bf52d2f7b2b05cd2dc918
http://arxiv.org/abs/2110.07911
http://arxiv.org/abs/2110.07911