Fetching the paper…
Reading the bibliography…
The shape of many objects in the built environment is dictated by their relationships to the human body: how will a person interact with this object? Existing data-driven generative models of 3D shapes produce plausible objects but do not reason about the relationship of those objects to the human body.
Scenegrok: Inferring action maps in 3d environments
Manolis Savva, Angel X. Chang, Pat Hanrahan, Matthew Fisher, and Matthias Nießner · 2014
Earlier work this paper cites.
Pose-conditioned joint angle limits for 3d human pose reconstruction
Ijaz Akhter and Michael J. Black · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
SMPL: A skinned multi-person linear model
Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2015
Earlier work this paper cites.
3d shapenets for 2.5d object recognition and next-best-view prediction
Zhirong Wu, Shuran Song, Aditya Khosla, Xiaoou Tang, and Jianxiong Xiao · 2015
Earlier work this paper cites.
PiGraphs: Learning Interaction Snapshots from Observations
Manolis Savva, Angel X. Chang, Pat Hanrahan, Matthew Fisher, and Matthias Nießner · 2016
Earlier work this paper cites.
Capturing hands in action using discriminative salient points and physics simulation
Dimitrios Tzionas, Luca Ballan, Abhilash Srikantha, Pablo Aponte, Marc Pollefeys, and Juergen Gall · 2016
Earlier work this paper cites.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, William T Freeman, and Joshua B Tenenbaum · 2016
Earlier work this paper cites.
Inferring forces and learning human utilities from videos
Yixin Zhu, Chenfanfu Jiang, Yibiao Zhao, Demetri Terzopoulos, and Song-Chun Zhu · 2016
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Earlier work this paper cites.
Grass: Generative recursive autoencoders for shape structures
Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang, and Leonidas Guibas · 2017
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3D classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Cited alongside, same era.
3d-prnn: Generating shape primitives with recurrent neural networks
Chuhang Zou, Ersin Yumer, Jimei Yang, Duygu Ceylan, and Derek Hoiem · 2017
Cited alongside, same era.
Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J. Guibas · 2018
Cited alongside, same era.
Functionality Representations and Applications for Shape Analysis
Ruizhen Hu, Manolis Savva, and Oliver van Kaick · 2018
Cited alongside, same era.
Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, and Aaron C. Courville · 2018
Cited alongside, same era.
Adaptive O-CNN: A patch-based deep representation of 3d shapes
Structurenet: Hierarchical graph networks for 3d shape generation
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, and Leonidas Guibas · 2019
Later among the works it cites.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Later among the works it cites.
Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge J. Belongie, and Bharath Hariharan · 2019
Later among the works it cites.
Fast tetrahedral meshing in the wild
Yixin Hu, Teseo Schneider, Bolun Wang, Denis Zorin, and Daniele Panozzo · 2020
Later among the works it cites.
Shapeassembly: Learning to generate programs for 3d shape structure synthesis
R. Kenny Jones, Theresa Barton, Xianghao Xu, Kai Wang, Ellen Jiang, Paul Guerrero, Niloy Mitra, and Daniel Ritchie · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Peng-Shuai Wang, Chun-Yu Sun, Yang Liu, and Xin Tong · 2018
Cited alongside, same era.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Cited alongside, same era.
Sdm-net: Deep generative network for structured deformable mesh
Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, and Hao Zhang · 2019
Cited alongside, same era.
Resolving 3D human pose ambiguities with 3D scene constraints
Mohamed Hassan, Vasileios Choutas, Dimitrios Tzionas, and Michael J. Black · 2019
Cited alongside, same era.
AMASS: Archive of motion capture as surface shapes
Naureen Mahmood, Nima Ghorbani, Nikolaus F. Troje, Gerard Pons-Moll, and Michael J. Black · 2019
Cited alongside, same era.
Simple and effective deep hand shape and pose regression from a single depth image
Jameel Malik, Ahmed Elhayek, Fabrizio Nunnari, and Didier Stricker · 2019
Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Jie Yang, Kaichun Mo, Yu-Kun Lai, Leonidas J Guibas, and Lin Gao · 2020
Later among the works it cites.
Stochastic scene-aware motion prediction
Mohamed Hassan, Duygu Ceylan, Ruben Villegas, Jun Saito, Jimei Yang, Yi Zhou, and Michael J Black · 2021
Closest in time.
Populating 3D scenes by learning human-scene interaction
Mohamed Hassan, Partha Ghosh, Joachim Tesch, Dimitrios Tzionas, and Michael J. Black · 2021
Closest in time.
Sp-gan: Sphere-guided 3d shape generation and manipulation
Ruihui Li, Xianzhi Li, Ke-Hei Hui, and Chi-Wing Fu · 2021
Closest in time.
Deep implicit moving least-squares functions for 3d reconstruction
Shi-Lin Liu, Hao-Xiang Guo, Hao Pan, Pengshuai Wang, Xin Tong, and Yang Liu · 2021
Closest in time.
Physically-aware generative network for 3d shape modeling
Mariem Mezghanni, Malika Boulkenafed, Andre Lieutier, and Maks Ovsjanikov · 2021
Closest in time.