Fetching the paper…
Reading the bibliography…
Traditional 3D scene understanding approaches rely on labeled 3D datasets to train a model for a single task with supervision.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Incremental dense semantic stereo fusion for large-scale semantic scene reconstruction
Vibhav Vineet, Ondrej Miksik, Morten Lidegaard, Matthias Nießner, Stuart Golodetz, Victor A Prisacariu, Olaf Kähler, David W Murray, Shahram Izadi, Patrick Pérez, et al · 2015
Earlier work this paper cites.
3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
Earlier work this paper cites.
Scenenn: A scene meshes dataset with annotations
Binh-Son Hua, Quang-Hieu Pham, Duc Thanh Nguyen, Minh-Khoi Tran, Lap-Fai Yu, and Sai-Kit Yeung · 2016
Earlier work this paper cites.
Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
Earlier work this paper cites.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
Earlier work this paper cites.
Semanticfusion: Dense 3d semantic mapping with convolutional neural networks
John McCormac, Ankur Handa, Andrew Davison, and Stefan Leutenegger · 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
Earlier work this paper cites.
O-cnn: Octree-based convolutional neural networks for 3d shape analysis
Peng-Shuai Wang, Yang Liu, Yu-Xiao Guo, Chun-Yu Sun, and Xin Tong · 2017
Earlier work this paper cites.
Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans
Angela Dai, Daniel Ritchie, Martin Bokeloh, Scott Reed, Jürgen Sturm, and Matthias Nießner · 2018
Earlier work this paper cites.
Tangent convolutions for dense prediction in 3d
Maxim Tatarchenko, Jaesik Park, Vladlen Koltun, and Qian-Yi Zhou · 2018
Earlier work this paper cites.
Semantickitti: A dataset for semantic scene understanding of lidar sequences
Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, and Jurgen Gall · 2019
Earlier work this paper cites.
Mitigating the hubness problem for zero-shot learning of 3d objects
Ali Cheraghian, Shafin Rahman, Dylan Campbell, and Lars Petersson · 2019
Earlier work this paper cites.
Zero-shot learning of 3d point cloud objects
Ali Cheraghian, Shafin Rahman, and Lars Petersson · 2019
Earlier work this paper cites.
4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
Earlier work this paper cites.
Texturenet: Consistent local parametrizations for learning from high-resolution signals on meshes
Jingwei Huang, Haotian Zhang, Li Yi, Thomas Funkhouser, Matthias Nießner, and Leonidas J Guibas · 2019
Earlier work this paper cites.
Putting humans in a scene: Learning affordance in 3d indoor environments
Xueting Li, Sifei Liu, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, and Jan Kautz · 2019
Earlier work this paper cites.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke et al · 2019
Earlier work this paper cites.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
Earlier work this paper cites.
Scanrefer: 3d object localization in rgb-d scans using natural language
Dave Zhenyu Chen, Angel X Chang, and Matthias Nießner · 2020
Cited alongside, same era.
Transductive zero-shot learning for 3d point cloud classification
Ali Cheraghian, Shafin Rahman, Dylan Campbell, and Lars Petersson · 2020
Cited alongside, same era.
Occuseg: Occupancy-aware 3d instance segmentation
Lei Han, Tian Zheng, Lan Xu, and Lu Fang · 2020
Cited alongside, same era.
Virtual multi-view fusion for 3d semantic segmentation
Abhijit Kundu, Xiaoqi Yin, Alireza Fathi, David Ross, Brian Brewington, Thomas Funkhouser, and Caroline Pantofaru · 2020
Cited alongside, same era.
Mseg: A composite dataset for multi-domain semantic segmentation
John Lambert, Zhuang Liu, Ozan Sener, James Hays, and Vladlen Koltun · 2020
Cited alongside, same era.
Dualconvmesh-net: Joint geodesic and euclidean convolutions on 3d meshes
Jonas Schult, Francis Engelmann, Theodora Kontogianni, and Bastian Leibe · 2020
Self-supervised global-local structure modeling for point cloud domain adaptation with reliable voted pseudo labels
Hehe Fan, Xiaojun Chang, Wanyue Zhang, Yi Cheng, Ying Sun, and Mohan Kankanhalli · 2022
Closest in time.
Open-vocabulary image segmentation
Golnaz Ghiasi, Xiuye Gu, Yin Cui, and Tsung-Yi Lin · 2022
Closest in time.
Open-vocabulary object detection via vision and language knowledge distillation
Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, and Yin Cui · 2022
Closest in time.
Semantic abstraction: Open-world 3d scene understanding from 2d vision-language models
Huy Ha and Shuran Song · 2022
Closest in time.
Language-driven semantic segmentation
Boyi Li, Kilian Q Weinberger, Serge Belongie, Vladlen Koltun, and René Ranftl · 2022
Closest in time.
Panoptic-phnet: Towards real-time and high-precision lidar panoptic segmentation via clustering pseudo heatmap
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
Cited alongside, same era.
Learning 3d semantic scene graphs from 3d indoor reconstructions
Johanna Wald, Helisa Dhamo, Nassir Navab, and Federico Tombari · 2020
Cited alongside, same era.
3d affordancenet: A benchmark for visual object affordance understanding
Shengheng Deng, Xun Xu, Chaozheng Wu, Ke Chen, and Kui Jia · 2021
Cited alongside, same era.
Learning 3d semantic segmentation with only 2d image supervision
Kyle Genova, Xiaoqi Yin, Abhijit Kundu, Caroline Pantofaru, Forrester Cole, Avneesh Sud, Brian Brewington, Brian Shucker, and Thomas Funkhouser · 2021
Cited alongside, same era.
Bidirectional projection network for cross dimension scene understanding
Wenbo Hu, Hengshuang Zhao, Li Jiang, Jiaya Jia, and Tien-Tsin Wong · 2021
Cited alongside, same era.
Vmnet: Voxel-mesh network for geodesic-aware 3d semantic segmentation
Zeyu Hu, Xuyang Bai, Jiaxiang Shang, Runze Zhang, Jiayu Dong, Xin Wang, Guangyuan Sun, Hongbo Fu, and Chiew-Lan Tai · 2021
Cited alongside, same era.
Jinke Li, Xiao He, Yang Wen, Yuan Gao, Xiaoqiang Cheng, and Dan Zhang · 2022
Closest in time.
Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d
Yiyi Liao, Jun Xie, and Andreas Geiger · 2022
Closest in time.
Open-vocabulary semantic segmentation with frozen vision-language models
Chaofan Ma, Yuhuan Yang, Yanfeng Wang, Ya Zhang, and Weidi Xie · 2022
Closest in time.
Denseclip: Language-guided dense prediction with context-aware prompting
Yongming Rao, Wenliang Zhao, Guangyi Chen, Yansong Tang, Zheng Zhu, Guan Huang, Jie Zhou, and Jiwen Lu · 2022
Closest in time.
Learning multi-view aggregation in the wild for large-scale 3d semantic segmentation
Damien Robert, Bruno Vallet, and Loic Landrieu · 2022
Closest in time.
Language-grounded indoor 3d semantic segmentation in the wild
David Rozenberszki, Or Litany, and Angela Dai · 2022
Closest in time.
Image-to-lidar self-supervised distillation for autonomous driving data
Corentin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, and Renaud Marlet · 2022
Closest in time.
Clip-fields: Weakly supervised semantic fields for robotic memory
Nur Muhammad Mahi Shafiullah, Chris Paxton, Lerrel Pinto, Soumith Chintala, and Arthur Szlam · 2022
Closest in time.
Detr3d: 3d object detection from multi-view images via 3d-to-2d queries
Yue Wang, Vitor Campagnolo Guizilini, Tianyuan Zhang, Yilun Wang, Hang Zhao, and Justin Solomon · 2022
Closest in time.
Groupvit: Semantic segmentation emerges from text supervision
Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, and Xiaolong Wang · 2022
Closest in time.
Lidarmultinet: Towards a unified multi-task network for lidar perception
Dongqiangzi Ye, Zixiang Zhou, Weijia Chen, Yufei Xie, Yu Wang, Panqu Wang, and Hassan Foroosh · 2022
Closest in time.
Open-vocabulary semantic segmentation using test-time distillation
Nir Zabari and Yedid Hoshen · 2022
Closest in time.
Pointclip: Point cloud understanding by clip
Renrui Zhang, Ziyu Guo, Wei Zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, and Hongsheng Li · 2022
Closest in time.
Extract free dense labels from clip
Chong Zhou, Chen Change Loy, and Bo Dai · 2022
Closest in time.
F-vlm: Open-vocabulary object detection upon frozen vision and language models
Weicheng Kuo, Yin Cui, Xiuye Gu, AJ Piergiovanni, and Anelia Angelova · 2023
Closest in time.
Open-vocabulary semantic segmentation with mask-adapted clip
Feng Liang, Bichen Wu, Xiaoliang Dai, Kunpeng Li, Yinan Zhao, Hang Zhang, Peizhao Zhang, Peter Vajda, and Diana Marculescu · 2023
Closest in time.