[1] Wu S H, Sun W, Long P X et al. Quality-driven Poisson-guided autoscanning[J]. ACM Transactions on Graphics, 33, 1-12(2014).

[2] Su X Y, Zhang Q C, Chen W J. Three-dimensional imaging based on structured illumination[J]. Chinese Journal of Lasers, 41, 0209001(2014).

[3] Zhang Q C, Wu Z J. Three-dimensional imaging technique based on Gray-coded structured illumination[J]. Infrared and Laser Engineering, 49, 0303004(2020).

[4] Li B W, An Y T, Cappelleri D et al. High-accuracy, high-speed 3D structured light imaging techniques, and potential applications in intelligent robotics[J]. International Journal of Intelligent Robotics and Applications, 1, 86-103(2017).

[5] Wu Z, Kou Z. 3D reconstruction of a scene based on monocular multi-view image[J]. Optics & Optoelectronic Technology, 18, 51-56(2020).

[6] Chen R, Han S F, Xu J et al. Point-based multi-view stereo network[C], 1538-1547(2020).

[7] Ji Y, Ye J W, Yu J Y. Reconstructing gas flows using light-path approximation[C], 2507-2514(2013).

[8] Atcheson B, Ihrke I, Heidrich W et al. Time-resolved 3D capture of non-stationary gas flows[C], 1-9(2008).

[9] Ihrke I, Magnor M. Image-based tomographic reconstruction of flames[C], 365-373(2004).

[10] Wu Z H, Zhou Z, Tian D L et al. The reconstruction of three-dimensional flame with color temperature[J]. The Visual Computer, 31, 613-625(2015).

[11] Han K, Wong K Y K, Liu M M. A fixed viewpoint approach for dense reconstruction of transparent objects[C], 4001-4008(2015).

[12] Han K, Wong K Y K, Liu M M. Dense reconstruction of transparent objects by altering incident light paths through refraction[J]. International Journal of Computer Vision, 126, 460-475(2018).

[13] Sun Z, Qiao Y, Jiang Z G et al. An accurate Fourier-based method for three-dimensional reconstruction of transparent surfaces in the shape-from-polarization method[J]. IEEE Access, 8, 42097-42110(2020).

[14] Drouet F, Stolz C, Laligant O et al. 3D reconstruction of external and internal surfaces of transparent objects from the polarization state of highlights[J]. Optics Letters, 39, 2955-2958(2014).

[15] Guo H Y, Zhou H W, Banerjee P P. Surface shape reconstruction of transparent objects using structured light[C], DTh5C.4(2021).

[16] He K J, Sui C Y, Huang T Y et al. 3D surface reconstruction of transparent objects using laser scanning with a four-layers refinement process[J]. Optics Express, 30, 8571-8591(2022).

[17] Laurentini A. The visual hull concept for silhouette-based image understanding[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16, 150-162(1994).

[18] Ben-Ezra, Nayar. What does the motion reveal about transparency?[C], 1025-1032(2008).

[19] Kutulakos K N, Steger E. A theory of refractive and specular 3D shape by light-path triangulation[J]. International Journal of Computer Vision, 76, 13-29(2008).

[20] Qian Y M, Gong M L, Yang Y H. 3D reconstruction of transparent objects with position-normal consistency[C], 4369-4377(2016).

[21] Wu B J, Zhou Y, Qian Y M et al. Full 3D reconstruction of transparent objects[J]. ACM Transactions on Graphics, 37, 1-11(2018).

[22] Miyazaki D, Ikeuchi K. The shape estimation of transparent objects by using the inverse polarization ray tracing[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 2018-2029(2007).

[23] Kim J, Reshetouski I, Ghosh A. Acquiring axially-symmetric transparent objects using single-view transmission imaging[C], 1484-1492(2017).

[24] Lü J H, Wu B J, Lischinski D et al. Differentiable refraction-tracing for mesh reconstruction of transparent objects[J]. ACM Transactions on Graphics, 39, 1-13(2020).

[25] Bruss A R, Horn B K P. Passive navigation[J]. Computer Vision, Graphics, and Image Processing, 21, 3-20(1983).

[26] Chen G Y, Han K, Wong K Y K. TOM-net: learning transparent object matting from a single image[C], 9233-9241(2018).

[27] Stets J, Li Z Q, Frisvad J R et al. Single-shot analysis of refractive shape using convolutional neural networks[C], 995-1003(2019).

[28] Sajjan S, Moore M, Pan M K et al. Clear grasp: 3D shape estimation of transparent objects for manipulation[C], 3634-3642(2020).

[29] Zhang Y D, Funkhouser T. Deep depth completion of a single RGB-D image[C], 175-185(2018).

[30] Blender. Blender physics engine[EB/OL]. https://docs.blender.org/manual/en/latest/physics/index.html.3

[31] Blender. Blender cycles[EB/OL]. https://docs.blender.org/manual/en/2.80/render/cycles/introduction.html.3

[32] Xu H P, Wang Y R, Eppel S et al. Seeing glass: joint point cloud and depth completion for transparent objects[EB/OL]. https://arxiv.org/abs/2110.00087

[33] Dai Q Y, Zhang J Y, Li Q W et al. Domain randomization-enhanced depth simulation and restoration for perceiving and grasping specular and transparent objects[M]. Avidan S, Brostow G, Cissé M, et al. Computer vision-ECCV 2022, 13699, 374-391(2022).

[34] Jiang J Q, Cao G Q, Do T et al. A4T: hierarchical affordance detection for transparent objects depth reconstruction and manipulation[J]. IEEE Robotics and Automation Letters, 7, 9826-9833(2022).

[35] Chen K, Wang S C, Xia B H et al. TODE-trans: transparent object depth estimation with a transformer[EB/OL]. https://arxiv.org/abs/2209.08455

[36] Vaswani A, Shazeer N, Parmar N et al. Attention is all You need[C], 6000-6010(2017).

[37] Liu Z, Lin Y T, Cao Y et al. Swin transformer: hierarchical vision transformer using shifted windows[C], 9992-10002(2022).

[38] Tang Y J, Chen J H, Yang Z G et al. DepthGrasp: depth completion of transparent objects using self-attentive adversarial network with spectral residual for grasping[C], 5710-5716(2021).

[39] Goodfellow I, Pouget-Abadie J, Mirza M et al. Generative adversarial networks[J]. Communications of the ACM, 63, 139-144(2020).

[40] Fang H J, Fang H S, Xu S et al. TransCG: a large-scale real-world dataset for transparent object depth completion and a grasping baseline[EB/OL]. https://arxiv.org/abs/2202.08471

[41] Huang G, Liu Z, Van Der Maaten L et al. Densely connected convolutional networks[C], 2261-2269(2017).

[42] Zhu L Y, Mousavian A, Xiang Y et al. RGB-D local implicit function for depth completion of transparent objects[C], 4647-4656(2021).

[43] Mildenhall B, Srinivasan P, Tancik M et al. NeRF[J]. Communications of the ACM, 65, 99-106(2022).

[44] Liu L, Gu J, Zaw Lin K et al. Neural sparse voxel fields[J]. Advances in Neural Information Processing Systems, 33, 15651-15663(2020).

[45] Schwarz K, Liao Y, Niemeyer M et al. GRAF: generative radiance fields for 3D-aware image synthesis[C], 20154-20166(2020).

[46] Ichnowski J, Avigal Y, Kerr J et al. Dex-NeRF: using a neural radiance field to grasp transparent objects[EB/OL]. https://arxiv.org/abs/2110.14217

[47] Dai Q Y, Zhu Y, Geng Y R et al. GraspNeRF: multiview-based 6-DoF grasp detection for transparent and specular objects using generalizable NeRF[EB/OL]. https://arxiv.org/abs/2210.06575

[48] Li Z Q, Yeh Y, Chandraker M. Through the looking glass: neural 3D reconstruction of transparent shapes[C], 1259-1268(2020).

[49] Chen X T, Zhang H J, Yu Z R et al. ClearPose: large-scale transparent object dataset and benchmark[M]. Avidan S, Brostow G, Cissé M, et al. Computer vision-ECCV 2022, 13668, 381-396(2022).

[50] Liu X Y, Jonschkowski R, Angelova A et al. KeyPose: multi-view 3D labeling and keypoint estimation for transparent objects[C], 11599-11607(2020).