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Can 3D Vision-Language Models Truly Understand Natural Language?

, , , , , , и . CoRR, (2024)

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Jihan Khoder

Jihan Mohasseb

Yang Yang

Yang Yang

Yang Yang

 

Другие публикации лиц с тем же именем

ST3D: Self-Training for Unsupervised Domain Adaptation on 3D Object Detection., , , , и . CVPR, стр. 10368-10378. Computer Vision Foundation / IEEE, (2021)PLA: Language-Driven Open-Vocabulary 3D Scene Understanding., , , , , и . CVPR, стр. 7010-7019. IEEE, (2023)An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation., , , , , , и . CoRR, (2019)Knowledge Distillation as Efficient Pre-training: Faster Convergence, Higher Data-efficiency, and Better Transferability., , , , и . CVPR, стр. 9151-9161. IEEE, (2022)Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation., , и . ICCV, стр. 6910-6920. IEEE, (2021)An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation., , , , , , и . AAAI, стр. 12613-12620. AAAI Press, (2020)Towards Efficient 3D Object Detection with Knowledge Distillation., , , , и . NeurIPS, (2022)DODA: Data-Oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation., , , и . ECCV (27), том 13687 из Lecture Notes in Computer Science, стр. 284-303. Springer, (2022)Can 3D Vision-Language Models Truly Understand Natural Language?, , , , , , и . CoRR, (2024)RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding., , , и . CoRR, (2023)