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DTSTAMP:20250522T212948Z
LOCATION:Mile High 2A
DTSTART;TZID=America/Denver:20240731T140000
DTEND;TZID=America/Denver:20240731T153000
UID:siggraph_SIGGRAPH 2024_sess131@linklings.com
SUMMARY:3D Shape Analysis
DESCRIPTION:3D Shape Analysis - Interactive Discussion\n\nAfter the summar
 y presentations, attendees will participate in an interactive discussion. 
 Distributed around the room will be a series of poster boards for authors 
 to gather around with the audience. Authors are invited to bring any mater
 ial related to their paper that could instigate further conver...\n\n-----
 ----------------\nDiffCAD: Weakly-supervised Probabilistic CAD Model Retri
 eval and Alignment From an RGB Image\n\nDiffCAD introduces probabilistic C
 AD retrieval and alignment to an RGB image. It models the disentangled dis
 tributions of scene scale, object pose, and shape leveraging diffusion. Th
 is enables cross-domain multi hypothesis CAD reconstruction, capturing the
  inherent ambiguities in depth/scale and obj...\n\n\nDaoyi Gao, David Roze
 nberszki, Stefan Leutenegger, and Angela Dai (Technical University of Muni
 ch)\n---------------------\n3Doodle: Compact Abstraction of Objects With 3
 D Strokes\n\nWe propose 3Doodle, a compact and efficient representation to
  convey characteristics of an object. Our approach generates 3D strokes fr
 om multi-view images. We express 3D sketch with contour of superquadrics (
 view-dependent component) and 3D cubic Bezier curves (view-independent com
 ponent). 3Doodle ...\n\n\nChangwoon Choi, Jaeah Lee, Jaesik Park, and Youn
 g Min Kim (Seoul National University)\n---------------------\nDAE-Net: Def
 orming Auto-Encoder for Fine-grained Shape Co-segmentation\n\nWe present a
 n unsupervised 3D shape co-segmentation method following the stipulation t
 hat corresponding parts in different shapes should have approximately the 
 same shape. Our method learns the shapes of a set of part templates and co
 mposes each shape by selecting a subset of template parts which ar...\n\n\
 nZhiqin Chen (Adobe Research) and Qimin Chen, Hang Zhou, and Hao Zhang (Si
 mon Fraser University)\n---------------------\nSplit-and-Fit: Learning B-R
 eps via Structure-aware Voronoi Partitioning\n\nThe "Split-and-Fit" method
  introduces a top-down, structure-aware strategy for reconstructing B-Rep 
 models, using Voronoi diagrams to partition the space and followed by prim
 itive fitting. We design NVD-Net to accurately predict these partitions fr
 om point clouds or distance fields, resulting in sig...\n\n\nYilin Liu (Sh
 enzhen University, Simon Fraser University); Jiale Chen and Shanshan Pan (
 Shenzhen University); Daniel Cohen-Or (Tel Aviv University, Shenzhen Unive
 rsity); Hao Zhang (Simon Fraser University); and Hui Huang (Shenzhen Unive
 rsity)\n---------------------\nImplicit Swept Volume SDF: Enabling Continu
 ous Collision-free Trajectory Generation for Arbitrary Shapes\n\nOur innov
 ative approach to trajectory generation seamlessly navigates the complexit
 ies of continuous collision avoidance for objects in challenging environme
 nts. Leveraging the Swept Volume Signed Distance Field, our hierarchical p
 ipeline outperforms traditional methods by deftly handling non-convex...\n
 \n\nJingping Wang and Tingrui Zhang (Zhejiang University); Qixuan Zhang an
 d Chuxiao Zeng (ShanghaiTech University, Deemos Technology); Jingyi Yu (Sh
 anghaiTech University); Chao Xu (Zhejiang University); Lan Xu (ShanghaiTec
 h University); and Fei Gao (Zhejiang University)\n---------------------\nV
 ariational Feature Extraction in Scientific Visualization\n\nFeature extra
 ction is a common approach to analyze large scientific data sets. At prese
 nt, many extraction techniques exist in different application domains. Usi
 ng variational calculus, we phrase common feature definitions in a consist
 ent mathematical language. We apply our framework in fluid dynami...\n\n\n
 Nico Daßler and Tobias Günther (University of Erlangen-Nuremberg)\n\nInter
 est Area: Research & Education\n\nKeyword: Geometry, Modeling\n\nRegistrat
 ion Category: Full Conference, Full Conference Supporter, Virtual Access, 
 Exhibitor Full Conference, Wednesday\n\nSession Chair: Siddhartha Chaudhur
 i (Adobe)
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