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In embodied vision, Instance ImageGoal Navigation (IIN) requires an agent to locate a specific object depicted in a goal image within an unexplored environment.
B. Yamauchi, “A frontier-based approach for autonomous exploration,” in
1997
Earlier work this paper cites.
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in
2009
Earlier work this paper cites.
D. Holz, N. Basilico, F. Amigoni, and S. Behnke, “Evaluating the efficiency of frontier-based exploration strategies,” in
2010
Earlier work this paper cites.
M. Juliá, A. Gil, and O. Reinoso, “A comparison of path planning strategies for autonomous exploration and mapping of unknown environments,”
2012
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,”
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
K. He, G. Gkioxari, P. Dollár, and R. Girshick, “Mask r-cnn,” in
2017
Earlier work this paper cites.
Y. Zhu, R. Mottaghi, E. Kolve, J. J. Lim, A. Gupta, L. Fei-Fei, and A. Farhadi, “Target-driven visual navigation in indoor scenes using deep reinforcement learning,” in
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
F. Xia, A. R. Zamir, Z. He, A. Sax, J. Malik, and S. Savarese, “Gibson env: Real-world perception for embodied agents,” in
2018
Earlier work this paper cites.
N. Savinov, A. Dosovitskiy, and V. Koltun, “Semi-parametric topological memory for navigation,”
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
M. Savva, A. Kadian, O. Maksymets, Y. Zhao, E. Wijmans, B. Jain, J. Straub, J. Liu, V. Koltun, J. Malik
2019
Earlier work this paper cites.
Y. Wu, Y. Wu, A. Tamar, S. Russell, G. Gkioxari, and Y. Tian, “Bayesian relational memory for semantic visual navigation,” in
2019
Earlier work this paper cites.
X. Wang, Q. Huang, A. Celikyilmaz, J. Gao, D. Shen, Y.-F. Wang, W. Y. Wang, and L. Zhang, “Vision-language navigation policy learning and adaptation,”
2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
D. S. Chaplot, D. P. Gandhi, A. Gupta, and R. R. Salakhutdinov, “Object goal navigation using goal-oriented semantic exploration,”
2020
Earlier work this paper cites.
B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng, “Nerf: Representing scenes as neural radiance fields for view synthesis,” in
2020
Earlier work this paper cites.
L. Liu, J. Gu, K. Zaw Lin, T.-S. Chua, and C. Theobalt, “Neural sparse voxel fields,”
2020
Earlier work this paper cites.
M. Chang, A. Gupta, and S. Gupta, “Semantic visual navigation by watching youtube videos,”
2020
Earlier work this paper cites.
S. Wani, S. Patel, U. Jain, A. Chang, and M. Savva, “Multion: Benchmarking semantic map memory using multi-object navigation,”
2020
Earlier work this paper cites.
D. S. Chaplot, R. Salakhutdinov, A. Gupta, and S. Gupta, “Neural topological slam for visual navigation,” in
2020
Earlier work this paper cites.
M. Tyszkiewicz, P. Fua, and E. Trulls, “Disk: Learning local features with policy gradient,” in
2020
Earlier work this paper cites.
Q. Cai, L. Zhang, Y. Wu, W. Yu, and D. Hu, “A pose-only solution to visual reconstruction and navigation,”
2021
Earlier work this paper cites.
B. Lin, Y. Zhu, Y. Long, X. Liang, Q. Ye, and L. Lin, “Adversarial reinforced instruction attacker for robust vision-language navigation,”
2021
Earlier work this paper cites.
A. Szot, A. Clegg, E. Undersander, E. Wijmans, Y. Zhao, J. Turner, N. Maestre, M. Mukadam, D. S. Chaplot, O. Maksymets
2021
Earlier work this paper cites.
D. S. Chaplot, M. Dalal, S. Gupta, J. Malik, and R. R. Salakhutdinov, “Seal: Self-supervised embodied active learning using exploration and 3D consistency,”
2021
Cited alongside, same era.
Y. Choi and S. Oh, “Image-goal navigation via keypoint-based reinforcement learning,” in
2021
Cited alongside, same era.
M. Hahn, D. S. Chaplot, S. Tulsiani, M. Mukadam, J. M. Rehg, and A. Gupta, “No rl, no simulation: Learning to navigate without navigating,”
2021
Cited alongside, same era.
2021
Cited alongside, same era.
W. Cheng, X. Dong, S. Khan, and J. Shen, “Learning disentanglement with decoupled labels for vision-language navigation,” in
2022
Cited alongside, same era.
B. Kerbl, G. Kopanas, T. Leimkühler, and G. Drettakis, “3D gaussian splatting for real-time radiance field rendering,”
2023
Later among the works it cites.
W. Wang, J. Dai, Z. Chen, Z. Huang, Z. Li, X. Zhu, X. Hu, T. Lu, L. Lu, H. Li
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
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J. Krantz and S. Lee, “Sim-2-sim transfer for vision-and-language navigation in continuous environments,” in
2022
Cited alongside, same era.
S. Zhang, W. Li, X. Song, Y. Bai, and S. Jiang, “Generative meta-adversarial network for unseen object navigation,” in
2022
Cited alongside, same era.
C. Lin, Y. Jiang, J. Cai, L. Qu, G. Haffari, and Z. Yuan, “Multimodal transformer with variable-length memory for vision-and-language navigation,” in
2022
Cited alongside, same era.
H. Wang, W. Liang, L. V. Gool, and W. Wang, “Towards versatile embodied navigation,” in
2022
Cited alongside, same era.
2022
Cited alongside, same era.
S. K. Ramakrishnan, D. S. Chaplot, Z. Al-Halah, J. Malik, and K. Grauman, “Poni: Potential functions for objectgoal navigation with interaction-free learning,” in
2022
Cited alongside, same era.
Z. Al-Halah, S. K. Ramakrishnan, and K. Grauman, “Zero experience required: Plug & play modular transfer learning for semantic visual navigation,” in
2022
Cited alongside, same era.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
H. Matsuki, R. Murai, P. H. J. Kelly, and A. J. Davison, “Gaussian splatting slam,”
2023
Later among the works it cites.
2023
Later among the works it cites.
P. Marza, L. Matignon, O. Simonin, and C. Wolf, “Multi-object navigation with dynamically learned neural implicit representations,” in
2023
Later among the works it cites.
2023
Later among the works it cites.
K. Yadav, R. Ramrakhya, A. Majumdar, V.-P. Berges, S. Kuhar, D. Batra, A. Baevski, and O. Maksymets, “Offline visual representation learning for embodied navigation,” in
2023
Later among the works it cites.
O. Kwon, J. Park, and S. Oh, “Renderable neural radiance map for visual navigation,” in
2023
Later among the works it cites.
S. Y. Gadre, M. Wortsman, G. Ilharco, L. Schmidt, and S. Song, “Cows on pasture: Baselines and benchmarks for language-driven zero-shot object navigation,” in
2023
Later among the works it cites.
T. Gervet, S. Chintala, D. Batra, J. Malik, and D. S. Chaplot, “Navigating to objects in the real world,”
2023
Later among the works it cites.
R. Liu, X. Wang, W. Wang, and Y. Yang, “Bird’s-eye-view scene graph for vision-language navigation,” in
2023
Later among the works it cites.
J. Zhang, L. Dai, F. Meng, Q. Fan, X. Chen, K. Xu, and H. Wang, “3D-aware object goal navigation via simultaneous exploration and identification,” in
2023
Later among the works it cites.
P. Lindenberger, P.-E. Sarlin, and M. Pollefeys, “Lightglue: Local feature matching at light speed,”
2023
Later among the works it cites.
R. Pautrat, I. Suárez, Y. Yu, M. Pollefeys, and V. Larsson, “GlueStick: Robust image matching by sticking points and lines together,” in
2023
Later among the works it cites.
D. An, H. Wang, W. Wang, Z. Wang, Y. Huang, K. He, and L. Wang, “Etpnav: Evolving topological planning for vision-language navigation in continuous environments,”
2024
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X. Lei, M. Wang, W. Zhou, L. Li, and H. Li, “Instance-aware exploration-verification-exploitation for instance imagegoal navigation,” in
2024
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G. Chen and W. Wang, “A survey on 3D gaussian splatting,”
2024
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2024
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H. Wang, A. G. H. Chen, X. Li, M. Wu, and H. Dong, “Find what you want: Learning demand-conditioned object attribute space for demand-driven navigation,”
2024
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S. Tan, K. Sima, D. Wang, M. Ge, D. Guo, and H. Liu, “Self-supervised 3D semantic representation learning for vision-and-language navigation,”
2024
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R. Liu, W. Wang, and Y. Yang, “Volumetric environment representation for vision-language navigation,” in
2024
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X. Sun, P. Chen, J. Fan, J. Chen, T. Li, and M. Tan, “Fgprompt: fine-grained goal prompting for image-goal navigation,” in
2024
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