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Recent advancements in multimodal pre-training have shown promising efficacy in 3D representation learning by aligning multimodal features across 3D shapes, their 2D counterparts, and language descriptions.
Monocular 3d scene understanding with explicit occlusion reasoning
Christian Wojek, Stefan Walk, Stefan Roth, and Bernt Schiele · 2011
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
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3D scientific visualization with Blender®
Brian R Kent · 2015
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Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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3d semantic parsing of large-scale indoor spaces
Iro Armeni, Ozan Sener, Amir R Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese · 2016
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Multi-modal auto-encoders as joint estimators for robotics scene understanding
Cesar Cadena, Anthony R Dick, and Ian D Reid · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Bottom-up and top-down attention for image captioning and visual question answering
Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, and Lei Zhang · 2018
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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten · 2018
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Neural baby talk
Jiasen Lu, Jianwei Yang, Dhruv Batra, and Devi Parikh · 2018
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Dgcnn: Disordered graph convolutional neural network based on the gaussian mixture model
Bo Wu, Yang Liu, Bo Lang, and Lei Huang · 2018
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Densepoint: Learning densely contextual representation for efficient point cloud processing
Yongcheng Liu, Bin Fan, Gaofeng Meng, Jiwen Lu, Shiming Xiang, and Chunhong Pan · 2019
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Grounded video description
Luowei Zhou, Yannis Kalantidis, Xinlei Chen, Jason J Corso, and Marcus Rohrbach · 2019
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Randla-net: Efficient semantic segmentation of large-scale point clouds
Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, and Andrew Markham · 2020
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Unified vision-language pre-training for image captioning and vqa
Luowei Zhou, Hamid Palangi, Lei Zhang, Houdong Hu, Jason Corso, and Jianfeng Gao · 2020
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Unifying vision-and-language tasks via text generation
Jaemin Cho, Jie Lei, Hao Tan, and Mohit Bansal · 2021
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Mvtn: Multi-view transformation network for 3d shape recognition
Abdullah Hamdi, Silvio Giancola, and Bernard Ghanem · 2021
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Seeing out of the box: End-to-end pre-training for vision-language representation learning
Zhicheng Huang, Zhaoyang Zeng, Yupan Huang, Bei Liu, Dongmei Fu, and Jianlong Fu · 2021
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Openclip, 2021
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt · 2021
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Vilt: Vision-and-language transformer without convolution or region supervision
Wonjae Kim, Bokyung Son, and Ildoo Kim · 2021
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Group-free 3d object detection via transformers
Pointnext: Revisiting pointnet++ with improved training and scaling strategies
Guocheng Qian, Yuchen Li, Houwen Peng, Jinjie Mai, Hasan Abed Al Kader Hammoud, Mohamed Elhoseiny, and Bernard Ghanem · 2022
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Surface representation for point clouds
Haoxi Ran, Jun Liu, and Chengjie Wang · 2022
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Softgroup for 3d instance segmentation on point clouds
Thang Vu, Kookhoi Kim, Tung M Luu, Thanh Nguyen, and Chang D Yoo · 2022
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P2p: Tuning pre-trained image models for point cloud analysis with point-to-pixel prompting
Ziyi Wang, Xumin Yu, Yongming Rao, Jie Zhou, and Jiwen Lu · 2022
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Ulip: Learning unified representation of language, image and point cloud for 3d understanding
Le Xue, Mingfei Gao, Chen Xing, Roberto Martín-Martín, Jiajun Wu, Caiming Xiong, Ran Xu, Juan Carlos Niebles, and Silvio Savarese · 2022
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Ze Liu, Zheng Zhang, Yue Cao, Han Hu, and Xin Tong · 2021
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An end-to-end transformer model for 3d object detection
Ishan Misra, Rohit Girdhar, and Armand Joulin · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Simvlm: Simple visual language model pretraining with weak supervision
Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, and Yuan Cao · 2021
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Center-based 3d object detection and tracking
Tianwei Yin, Xingyi Zhou, and Philipp Krahenbuhl · 2021
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Multi-grained vision language pre-training: Aligning texts with visual concepts
Yan Zeng, Xinsong Zhang, and Hang Li · 2021
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Objaverse: A universe of annotated 3d objects
Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli Vanderbilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, and Ali Farhadi · 2022
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Let images give you more: Point cloud cross-modal training for shape analysis
Xu Yan, Heshen Zhan, Chaoda Zheng, Jiantao Gao, Ruimao Zhang, Shuguang Cui, and Zhen Li · 2022
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Point-bert: Pre-training 3d point cloud transformers with masked point modeling
Xumin Yu, Lulu Tang, Yongming Rao, Tiejun Huang, Jie Zhou, and Jiwen Lu · 2022
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Pointclip v2: Prompting clip and gpt for powerful 3d open-world learning
Xiangyang Zhu, Renrui Zhang, Bowei He, Ziyu Guo, Ziyao Zeng, Zipeng Qin, Shanghang Zhang, and Peng Gao · 2022
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Clip2point: Transfer clip to point cloud classification with image-depth pre-training
Tianyu Huang, Bowen Dong, Yunhan Yang, Xiaoshui Huang, Rynson WH Lau, Wanli Ouyang, and Wangmeng Zuo · 2023
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Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
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Openshape: Scaling up 3d shape representation towards open-world understanding
Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li, Shizhong Han, Hong Cai, Fatih Porikli, and Hao Su · 2023
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Gpt-4 technical report
OpenAI · 2023
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Artemis Panagopoulou, Le Xue, Ning Yu, Junnan Li, Dongxu Li, Shafiq Joty, Ran Xu, Silvio Savarese, Caiming Xiong, and Juan Carlos Niebles · 2023
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Model-agnostic hierarchical attention for 3d object detection
Manli Shu, Le Xue, Ning Yu, Roberto Martín-Martín, Juan Carlos Niebles, Caiming Xiong, and Ran Xu · 2023
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X-InstructBLIP: A framework for aligning
Anonymous Submission · 2023
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Pointllm: Empowering large language models to understand point clouds
Runsen Xu, Xiaolong Wang, Tai Wang, Yilun Chen, Jiangmiao Pang, and Dahua Lin · 2023
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