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In recent years, increasing attention has been directed to leveraging pre-trained vision models for motor control.
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What matters in learning from offline human demonstrations for robot manipulation
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Habitat: A platform for embodied ai research
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An image is worth 16x16 words: Transformers for image recognition at scale
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Zhou, J., Wei, C., Wang, H., Shen, W., Xie, C., Yuille, A., and Kong, T · 2021
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Vicregl: Self-supervised learning of local visual features
Bardes, A., Ponce, J., and LeCun, Y · 2022
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Maskclip: Masked self-distillation advances contrastive language-image pretraining
Dong, X., Zheng, Y., Bao, J., Zhang, T., Chen, D., Yang, H., Zeng, M., Zhang, W., Yuan, L., Chen, D., et al · 2022
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Ego4d: Around the world in 3,000 hours of egocentric video
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Watch and match: Supercharging imitation with regularized optimal transport
Haldar, S., Mathur, V., Yarats, D., and Pinto, L · 2022
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On pre-training for visuo-motor control: Revisiting a learning-from-scratch baseline
Hansen, N., Yuan, Z., Ze, Y., Mu, T., Rajeswaran, A., Su, H., Xu, H., and Wang, X · 2022
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Masked autoencoders are scalable vision learners
He, K., Chen, X., Xie, S., Li, Y., Dollár, P., and Girshick, R · 2022
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Semantic-aware fine-grained correspondence
Hu, Y., Wang, R., Zhang, K., and Gao, Y · 2022
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Khandelwal, A., Weihs, L., Mottaghi, R., and Kembhavi, A · 2022
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Graph inverse reinforcement learning from diverse videos
Kumar, S., Zamora, J., Hansen, N., Jangir, R., and Wang, X · 2022
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A path towards autonomous machine intelligence
LeCun, Y · 2022
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Vip: Towards universal visual reward and representation via value-implicit pre-training
Ma, Y. J., Sodhani, S., Jayaraman, D., Bastani, O., Kumar, V., and Zhang, A · 2022
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Slip: Self-supervision meets language-image pre-training
Mu, N., Kirillov, A., Wagner, D., and Xie, S · 2022
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R3m: A universal visual representation for robot manipulation
Nair, S., Rajeswaran, A., Kumar, V., Finn, C., and Gupta, A · 2022
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The unsurprising effectiveness of pre-trained vision models for control
Parisi, S., Rajeswaran, A., Purushwalkam, S., and Gupta, A · 2022
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Beit v2: Masked image modeling with vector-quantized visual tokenizers
Peng, Z., Dong, L., Bao, H., Ye, Q., and Wei, F · 2022
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Radosavovic, I., Xiao, T., James, S., Abbeel, P., Malik, J., and Darrell, T · 2022
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Cliport: What and where pathways for robotic manipulation
Shridhar, M., Manuelli, L., and Fox, D · 2022
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Vrl3: A data-driven framework for visual deep reinforcement learning
Wang, C., Luo, X., Ross, K., and Li, D · 2022
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Masked visual pre-training for motor control
Xiao, T., Radosavovic, I., Darrell, T., and Malik, J · 2022
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Pre-trained image encoder for generalizable visual reinforcement learning
Yuan, Z., Xue, Z., Yuan, B., Wang, X., Wu, Y., Gao, Y., and Xu, H · 2022
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Zakka, K., Zeng, A., Florence, P., Tompson, J., Bohg, J., and Dwibedi, D · 2022
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