BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation | Paper Citation Record

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This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops

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This paper cites In: Proceedings of the IEEE conference on computer vision and pattern recognition.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition

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This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF international conference on computer vision

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This paper cites In: International Conference on Machine Learning.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: International Conference on Machine Learning

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This paper cites blender.org/, accessed: 10-08-2024.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation blender.org/, accessed: 10-08-2024

Reference 5

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This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 6

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This paper cites Matterport3D: Learning from RGB-D Data in Indoor Environments.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Matterport3D: Learning from RGB-D Data in Indoor Environments

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This paper cites ShapeNet: An Information-Rich 3D Model Repository.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation ShapeNet: An Information-Rich 3D Model Repository

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This paper cites arXiv preprint arXiv:2203.09065 (2022).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation arXiv preprint arXiv:2203.09065 (2022)

Reference 9

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This paper cites In: 2019 International Conference on 3D Vision (3DV).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2019 International Conference on 3D Vision (3DV)

Reference 10

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 11

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This paper cites In: 2017 international joint conference on neural networks (IJCNN).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2017 international joint conference on neural networks (IJCNN)

Reference 12

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 13

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This paper cites In: Proceedings of the European Conference on Computer Vision (ECCV).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the European Conference on Computer Vision (ECCV)

Reference 14

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This paper cites NeurIPS Datasets and Benchmarks 2(6), 16 (2021).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation NeurIPS Datasets and Benchmarks 2(6), 16 (2021)

Reference 15

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2009 IEEE conference on computer vision and pattern recognition

Reference 16

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This paper cites MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities

Reference 17

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This paper cites https://www.dotproduct3d.com/ dot3d.html, accessed: 10-08-2024.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation https://www.dotproduct3d.com/ dot3d.html, accessed: 10-08-2024

Reference 18

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This paper cites International journal of computer vision88, 303–338 (2010).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation International journal of computer vision88, 303–338 (2010)

Reference 19

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2004 conference on computer vision and pattern recognition workshop

Reference 20

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This paper cites A framework for benchmarking class-out-of-distribution detection and its application to ImageNet.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation A framework for benchmarking class-out-of-distribution detection and its application to ImageNet

Reference 21

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This paper cites In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Reference 22

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This paper cites Communications of the ACM 63(11), 139–144 (2020).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Communications of the ACM 63(11), 139–144 (2020)

Reference 23

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This paper cites Advances in neural information processing systems 30 (2017).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Advances in neural information processing systems 30 (2017)

Reference 24

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This paper cites IEEE transactions on pattern analysis and machine intelligence 43(12), 4338–4364 (2020).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation IEEE transactions on pattern analysis and machine intelligence 43(12), 4338–4364 (2020)

Reference 25

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This paper cites Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark

Reference 26

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 27

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 28

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Pro- ceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 29

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2016 fourth international conference on 3D vision (3DV)

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Unresolved cited work

Reference 31

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Pro- ceedings of the IEEE/CVF international conference on computer vision workshops

Reference 32

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This paper cites International Journal of Computer Vision126, 920–941 (2018).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation International Journal of Computer Vision126, 920–941 (2018)

Reference 33

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This paper cites PointSIFT: A SIFT-like Network Module for 3D Point Cloud Semantic Segmentation.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation PointSIFT: A SIFT-like Network Module for 3D Point Cloud Semantic Segmentation

Reference 34

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation but should vqa expect them to? In: Proceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition

Reference 35

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Auto-Encoding Variational Bayes

Reference 36

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 37

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops

Reference 38

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Master’s thesis, University of Tront (2009)

Reference 39

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 40

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This paper cites Current Opinion in Behavioral Sciences29, 97–104 (2019).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Current Opinion in Behavioral Sciences29, 97–104 (2019)

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation CS 231N7(7), 3 (2015)

Reference 42

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Proceedings of the IEEE86(11), 2278–2324 (1998) BelHouse3D 17

Reference 43

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: British Machine Vision Conference (BMVC) (2018)

Reference 44

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation arXiv e-prints pp

Reference 45

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 46

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This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence 45(3), 3292–3310 (2022).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation IEEE Transactions on Pattern Analysis and Machine Intelligence 45(3), 3292–3310 (2022)

Reference 47

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE international conference on computer vision

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings eighth IEEE international conference on com- puter vision

Reference 49

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This paper cites aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception

Reference 50

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:25.415648Z

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation OoDIS: Anomaly Instance Segmentation and Detection Benchmark

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2008 Sixth Indian conference on computer vision, graphics & image processing

Reference 53

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: International Conference on Med- ical Image Computing and Computer-Assisted Intervention

Reference 54

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Reference 55

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 56

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Reference 57

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 58

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This paper cites Advances in neural information processing systems 30 (2017) 18 U.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Advances in neural information processing systems 30 (2017) 18 U

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:25.272969Z

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This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 60

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 61

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This paper cites The International Journal of Robotics Research37(6), 545–557 (2018).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation The International Journal of Robotics Research37(6), 545–557 (2018)

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: European Conference on Computer Vision

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 2011 IEEE international conference on computer vision workshops (ICCV workshops)

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This paper cites Ad- vances in neural information processing systems30 (2017).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Ad- vances in neural information processing systems30 (2017)

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF international conference on computer vision

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This paper cites Advances in Neural Information Processing Systems34, 22221–22233 (2021).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Advances in Neural Information Processing Systems34, 22221–22233 (2021)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:25.130721Z

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:25.079961Z

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Unresolved cited work

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation ACM Transactions on Graphics (tog)38(5), 1–12 (2019)

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This paper cites Advances in Neural Information Processing Systems 35, 33330–33342 (2022).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Advances in Neural Information Processing Systems 35, 33330–33342 (2022)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:25.053386Z

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Observation eafd88c0-d44a-44d1-96b1-cdba058bf6d3 · outbound

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: 6th International Conference on Learning Repre- sentations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Workshop BelHouse3D 19 Track Proceedings

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:25.037290Z

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE conference on computer vision and pattern recognition

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the AAAI conference on artificial intelligence

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:25.008496Z

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Observation 6f1f3ea8-83dd-4a8a-8289-d74c7ae0e246 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE international conference on computer vision

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Observation b3831348-06d5-466e-9f41-0bba847416fa · outbound

This paper cites Differentially Private Generative Adversarial Network.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Differentially Private Generative Adversarial Network

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the European conference on computer vision (ECCV)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:24.854011Z

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Observation f03e925a-e68c-4d18-9a6e-4cd1fc81207e · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF International Conference on Computer Vision

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This paper cites IEEE journal of biomedical and health informatics24(8), 2378–2388 (2020).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation IEEE journal of biomedical and health informatics24(8), 2378–2388 (2020)

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Observation bef7c744-45ea-4f54-ba04-e26b3a74887e · outbound

This paper cites Transactions of the Association for Computational Linguistics2, 67–78 (2014).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation Transactions of the Association for Computational Linguistics2, 67–78 (2014)

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recog- nition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:24.825021Z

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Observation cc35ae5c-19d7-45f8-8763-768822def4ca · outbound

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF con- ference on computer vision and pattern recognition

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Observation e9768394-d850-464b-80ef-81ba119c2cef · outbound

This paper cites OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images

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Observation 8a1f7f1c-17a8-47c4-9536-19d0ee1902da · outbound

This paper cites In: European conference on computer vision.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: European conference on computer vision

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:24.742647Z

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Observation cd214e02-3c44-4173-8da5-60532d28fe2f · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:24.552662Z

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Observation 4d3c2655-64f7-43c8-a79d-0efb754afdb6 · outbound

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BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:24.544133Z

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Observation 8a558fe4-7ae0-44b8-a624-26082de11eb7 · outbound

This paper cites DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation

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Observation 5a5fe13f-65fe-4455-9dea-df90c2f9b43d · outbound

This paper cites In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part IX 16.

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part IX 16

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T16:43:24.535399Z

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Observation ccea6f67-85a7-45c8-a42f-125a95686a8b · outbound

This paper cites IEEE transactions on pattern analysis and machine intelligence 40(6), 1452–1464 (2017).

BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentation IEEE transactions on pattern analysis and machine intelligence 40(6), 1452–1464 (2017)

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