{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "PU28yIn4-PXC" }, "source": [ "# Single-Photon 3D Imaging with Equi-Depth Photon Histograms (ECCV24)\n", "\n", "This implemetation demonstrates how to use SPCSim to reproduce some of results from the paper \"Single-Photon 3D Imaging with Equi-Depth Photon Histograms\" [1]." ] }, { "cell_type": "markdown", "metadata": { "id": "LreLr97O-oF_" }, "source": [ "## EW histogram vs ED histogram\n", "\n", "Figure 2 of the paper compares the EW histogram and ED histogram for the same scene distance, illumination conditions and number of histogram bins." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "executionInfo": { "elapsed": 11171, "status": "ok", "timestamp": 1736711553430, "user": { "displayName": "Kaustubh Sadekar", "userId": "03721347199797132029" }, "user_tz": 480 }, "id": "-1hT-eCa-O5t" }, "outputs": [], "source": [ "from SPCSim.data_loaders.perpixel_loaders import PerPixelLoader\n", "from SPCSim.data_loaders.transient_loaders import TransientGenerator\n", "from SPCSim.utils.plot_utils import plot_transient, plot_ewh, plot_edh\n", "import matplotlib.pyplot as plt\n", "from SPCSim.sensors.dtof import RawSPC, BaseEWHSPC, BaseEDHSPC\n", "import torch\n", "import numpy as np\n", "\n", "\n", "# Simulating results for distance = 0.3*MaxDistance, for laser time period = 100ns\n", "# for average 0.1 signal photons per laser cycle and 0.2 background photons per laser cycle\n", "PixLdr = PerPixelLoader(\n", " min_dist = 0.3,\n", " tmax = 100, # in nano seconds\n", " sig_bkg_list = [[0.1,0.2]],\n", " device = \"cpu\" # Choosing to run on CPU\n", " )\n", "\n", "# Generate the per pixel data\n", "data = PixLdr.get_data()\n", "\n", "\n", "# Creating transient generator with laser time period of 100ns, FWHM (pulse width) 5ns and with\n", "# laser time period divided into 1000 equal time-bins\n", "tr_gen = TransientGenerator(Nr = PixLdr.Nr, Nc = PixLdr.Nc, N_tbins = 1000, tmax = PixLdr.tmax, FWHM = 5)\n", "\n", "\n", "# Using the get_transient function to generate the transient\n", "# for a given distance, albedo, intensity, and illumination condition\n", "phi_bar = tr_gen.get_transient(data[\"gt_dist\"],\n", " data[\"albedo\"], # By default albedo is just a array of ones\n", " data[\"albedo\"],\n", " data[\"alpha_sig\"],\n", " data[\"alpha_bkg\"])\n", "\n", "Nr, Nc, N_tbins = phi_bar.shape\n", "device = PixLdr.device\n", "seed_val = 43\n", "\n", "# Simulating data for 500 laser cycles\n", "N_pulses = 100\n", "\n", "# Setting RawSPC to return 500 timestamps per pixel over the total exposure time.\n", "# As RawSPC simulates single photon timestamp per laser cycle\n", "N_output_ts = N_pulses" ] }, { "cell_type": "markdown", "metadata": { "id": "HOX4E1h_FDH1" }, "source": [ "The `RawSPC` is used to simulate the photon time-stamps, `BaseEWHSPC` is used to capture corresponding equi-width histogram, and `BaseEDHSPC` class is used to capture the equi-depth histogram.\n", "\n", "`NOTE: Using the same non-zero seed value we can reproduce the poisson randomness in the photon timestamps.`" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "executionInfo": { "elapsed": 383, "status": "ok", "timestamp": 1736711859033, "user": { "displayName": "Kaustubh Sadekar", "userId": "03721347199797132029" }, "user_tz": 480 }, "id": "ewne_2piEsBL", "outputId": "17314335-d498-44cb-84ed-f16d17e7a514" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 100/100 [00:00<00:00, 7271.93it/s]\n", "100%|██████████| 100/100 [00:00<00:00, 7142.52it/s]\n", "100%|██████████| 100/100 [00:00<00:00, 5068.28it/s]\n" ] } ], "source": [ "spc1 = RawSPC(Nr,\n", " Nc,\n", " N_pulses,\n", " device,\n", " N_tbins,\n", " N_output_ts,\n", " seed=seed_val)\n", "\n", "# Captured data contains timestamps (Nr x Nc x N_output_ts)\n", "captured_data1 = spc1.capture(phi_bar)\n", "\n", "# Accessing the timestamp data\n", "raw_data = captured_data1[\"time_stamps\"]\n", "\n", "\n", "# Simulating data for 8-bin BaseEWHSPC sensor\n", "N_ewhbins = 8\n", "spc2 = BaseEWHSPC(\n", " Nr,\n", " Nc,\n", " N_pulses,\n", " device,\n", " N_tbins,\n", " N_ewhbins,\n", " seed=seed_val\n", " )\n", "\n", "# Captured data contains equi-width histogram (Nr x Nc x N_ewhbins)\n", "captured_data2 = spc2.capture(phi_bar)\n", "\n", "# Accessing the equi-width histogram\n", "ewh_data = captured_data2[\"ewh\"]\n", "\n", "# Simulating data for 8-bin BaseEDHSPC sensor\n", "N_edhbins = N_ewhbins\n", "spc3 = BaseEDHSPC(Nr,\n", " Nc,\n", " N_pulses,\n", " device,\n", " N_tbins,\n", " N_edhbins,\n", " seed=seed_val)\n", "\n", "# Captured data contains equi-depth histogram (Nr x Nc x N_ewhbins)\n", "captured_data3 = spc3.capture(phi_bar)\n", "\n", "# Accessing the equi-depth histogram\n", "oedh_data = captured_data3[\"oedh\"]" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 576 }, "executionInfo": { "elapsed": 964, "status": "ok", "timestamp": 1736711864909, "user": { "displayName": "Kaustubh Sadekar", "userId": "03721347199797132029" }, "user_tz": 480 }, "id": "d0z499VQEu8z", "outputId": "c4e3a769-86d4-4a98-897a-488352f7a9fa" }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plotting the results\n", "ROW, COL = [0,0]\n", "\n", "phi_bar1 = phi_bar[ROW, COL, :].cpu().numpy()\n", "ts = raw_data[ROW, COL, :].cpu().numpy().flatten()\n", "ewh1 = ewh_data[ROW, COL, :].cpu().numpy()\n", "edh1 = oedh_data[ROW, COL, :].cpu().numpy()\n", "\n", "ewh_bins_axis = torch.linspace(0,N_tbins-N_tbins//N_ewhbins,N_ewhbins)\n", "EDH_Height = (((data[\"alpha_sig\"][ROW,COL]+data[\"alpha_bkg\"][ROW,COL])*N_pulses/N_edhbins))\n", "\n", "\n", "fig1, (ax1, ax2) = plt.subplots(1,2,figsize = (10,3))\n", "plot_ewh(ax1, ewh_bins_axis, ewh1, label = \"EWH histogram\", color = 'w')\n", "plot_transient(ax1, phi_bar1*50*spc1.N_pulses, plt_type = '-r', label=\"True Transient\")\n", "ax1.plot(ts, np.random.rand(ts.shape[-1])*0.001-1,'xk', label='Photon timestamps', linewidth=1)\n", "csfont = {'fontname':'Times New Roman'}\n", "ax1.set_title(\"Equi-width histogram (EWH)\")\n", "ax1.set_xlabel(\"Discretized time (a.u.)\\n(a)\")\n", "ax1.set_ylabel(\"Photon counts\")\n", "ax1.spines['top'].set_visible(False)\n", "ax1.spines['right'].set_visible(False)\n", "\n", "ax2.set_title(\"Equi-depth histogram (EDH)\")\n", "# ax2.bar(edh1[:-1], EDH_Height, width = edh_widths,color='w', alpha=0.5, edgecolor = 'black', align = 'edge', linewidth=1)\n", "plot_edh(edh1,ax2,ymax = EDH_Height, colors_list=['k','k','k','k','k','k'])\n", "plot_transient(ax2, phi_bar1*50*spc1.N_pulses, plt_type = '-r', label=\"True Transient\")\n", "ax2.plot(ts, np.random.rand(ts.shape[-1])*0.001-1,'xk', label='Photon timestamps', linewidth=1)\n", "ax2.legend(frameon=False,fontsize=\"12\",loc='upper right')\n", "# ax2.set_ylim(top = EWH.max()*1.2)\n", "ax2.spines['top'].set_visible(False)\n", "ax2.spines['right'].set_visible(False)\n", "ax2.set_xlabel(\"Discretized time (a.u.)\\n(b)\")\n", "ax2.set_ylabel(\"Photon counts\")\n", "plt.gcf().set_dpi(200)\n", "# plt.tight_layout()\n", "fig1.savefig(\"Temp_Fig2.png\")" ] }, { "cell_type": "markdown", "metadata": { "id": "1L9Wb9n1GA0e" }, "source": [ "## Comparing binner stepping strategies\n", "\n", "We can use SPCSim to reproduce Figure 3 in the paper to compare the fixed stepping and optimized stepping binners." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 804 }, "executionInfo": { "elapsed": 3571, "status": "ok", "timestamp": 1736712257575, "user": { "displayName": "Kaustubh Sadekar", "userId": "03721347199797132029" }, "user_tz": 480 }, "id": "UoRVAtDOGp4Z", "outputId": "ab90ca3a-5b98-4bae-fe1b-fa395ebf2623" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2000\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 2000/2000 [00:01<00:00, 1379.01it/s]\n", "100%|██████████| 2000/2000 [00:01<00:00, 1556.21it/s]\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from SPCSim.utils.plot_utils import plot_transient, plot_edh, plot_edh_traj\n", "from SPCSim.sensors.dtof import HEDHBaseClass, PEDHOptimized\n", "from SPCSim.postproc.edh_postproc import PostProcEDH\n", "\n", "\n", "N_edhbins = 2 # Number of EDH bins\n", "N_pulses = 2000 # Number of laser pulses\n", "N_tbins = 1000 # Number of time bins per laser cycle (B)\n", "FWHM = 1 # in nano seconds\n", "device = \"cpu\" # Select the CPU/GPU device\n", "seed_val = 43\n", "\n", "# Simulating results for distance = 0.2*MaxDistance, for laser time period = 100ns\n", "# for average 1 signal photons per laser cycle and 1 background photons per laser cycle\n", "PixLdr = PerPixelLoader(\n", " min_dist = 0.2,\n", " tmax = 100, # in nano seconds\n", " sig_bkg_list = [[1,1]],\n", " device = \"cpu\" # Choosing to run on CPU\n", " )\n", "\n", "# Generate the per pixel data\n", "data = PixLdr.get_data()\n", "\n", "\n", "# Creating transient generator with laser time period of tmax ns, FWHM and with\n", "# laser time period divided into N_tbins equal time-bins\n", "tr_gen = TransientGenerator(Nr = PixLdr.Nr, Nc = PixLdr.Nc, N_tbins = N_tbins, tmax = PixLdr.tmax, FWHM = FWHM)\n", "\n", "\n", "# Using the get function to generate the transient\n", "# for a given distance, albedo, intensity, and illumination condition\n", "phi_bar = tr_gen.get_transient(data[\"gt_dist\"], # NOTE: the true distance is in meters and depends on tmax\n", " data[\"albedo\"],\n", " data[\"albedo\"],\n", " data[\"alpha_sig\"],\n", " data[\"alpha_bkg\"])\n", "\n", "# Set row and column of the pixel for which you want to track the CV trajectories\n", "ROW, COL = [0,0]\n", "\n", "# Initializing the HEDHBaseClass with desired sensor parameters\n", "spc1 = HEDHBaseClass(PixLdr.Nr,\n", " PixLdr.Nc,\n", " N_pulses,\n", " device,\n", " N_tbins,\n", " N_edhbins,\n", " pix_r = ROW,\n", " pix_c = COL,\n", " seed=seed_val,\n", " step_params={\n", " \"k\":1, # Step size gain\n", " \"step_vals\": [1], # List of reducing step size values per binner\n", " })\n", "\n", "# Capture method runs the HEDH binners for N_pulses based on the input true transient (phi_bar)\n", "captured_data1 = spc1.capture(phi_bar)\n", "\n", "# Extracting desired data components\n", "edh_data1 = captured_data1[\"edh\"].cpu().numpy() # Contains the binner output for selected EDH class\n", "gtedh_data1 = captured_data1[\"gtedh\"].cpu().numpy() # Contains the ground truth EDH computed using the true transient\n", "edh_list1 = captured_data1[\"traj\"] # Contains the binner trajectories for pixel at location\n", "edh_list1 = np.array(edh_list1)\n", "\n", "\n", "# Initializing the PEDHOptimized with desired sensor parameters and stepping params\n", "spc2 = PEDHOptimized(PixLdr.Nr,\n", " PixLdr.Nc,\n", " N_pulses,\n", " device,\n", " N_tbins,\n", " N_edhbins,\n", " pix_r = ROW,\n", " pix_c = COL,\n", " seed = seed_val,\n", " step_params={\n", " \"k\":3, # Step size gain\n", " \"decay\":0, # Setting decay = 0 allows to update final decay value as a function of N_pulses\n", " \"mtm\":0.8,\n", " \"min_clip\":0.02,\n", " \"switch_fraction\":0.8,\n", " \"delta_mem\": 0.95\n", " })\n", "\n", "# Capture method runs the HEDH binners for N_pulses based on the input true transient (phi_bar)\n", "captured_data2 = spc2.capture(phi_bar)\n", "\n", "# Extracting desired data components\n", "edh_data2 = captured_data2[\"edh\"].cpu().numpy() # Contains the binner output for selected EDH class\n", "gtedh_data2 = captured_data2[\"gtedh\"].cpu().numpy() # Contains the ground truth EDH computed using the true transient\n", "edh_list2 = captured_data2[\"traj\"] # Contains the binner trajectories for pixel at location\n", "edh_list2 = np.array(edh_list2)\n", "phi_bar = phi_bar[0,0,:].cpu().numpy()\n", "\n", "ewh_bins_axis = torch.linspace(0,N_tbins-1,N_tbins)\n", "\n", "fig1, ax1 = plt.subplots(1,1, figsize=(5,5))\n", "ax1.set_title(r'CV trajectories for different update strategies')\n", "ax1.plot(edh_list1, label=\"Fixed stepping\", alpha=0.5)\n", "ax1.plot(edh_list2,'-r',label=\"Optimized stepping\", alpha=0.6)\n", "ax1.plot(phi_bar*N_pulses,ewh_bins_axis, '-k', label=\"True Transient\")\n", "ax1.axhline(gtedh_data2[0,0,1], color = '#097969', label = \"True Median\")\n", "ax1.set_xlim(left = -0.5)\n", "ax1.set_xlim(left = 0, right = 1500)\n", "ax1.set_ylim(top = 520, bottom = 150)\n", "ax1.legend(fontsize=\"11\")\n", "plt.gcf().set_dpi(150)\n", "plt.tight_layout()\n", "fig1.savefig(\"Temp_Fig3.png\")\n" ] }, { "cell_type": "markdown", "metadata": { "id": "7a_wrBIHG-2a" }, "source": [ "## Post processing ED histograms\n", "\n", "The `edh_postproc` module of `postproc` subpackage provides `PostProcEDH` class to compute the photon density estimates and piecewise-constant $\\rho_0$ and piecewise-linear ($\\rho_1$) interpolated photon desntity estimates." ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 420 }, "executionInfo": { "elapsed": 28807, "status": "ok", "timestamp": 1736713237830, "user": { "displayName": "Kaustubh Sadekar", "userId": "03721347199797132029" }, "user_tz": 480 }, "id": "OblW6szjJjVg", "outputId": "c554d067-4edd-4e58-d7f2-1918ec96ea7d" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 5000/5000 [00:27<00:00, 179.39it/s]\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from SPCSim.data_loaders.perpixel_loaders import PerPixelLoader\n", "from SPCSim.data_loaders.transient_loaders import TransientGenerator\n", "import matplotlib.pyplot as plt\n", "from SPCSim.sensors.dtof import BaseEDHSPC, PEDHOptimized\n", "from SPCSim.postproc.edh_postproc import PostProcEDH\n", "import time\n", "import torch\n", "import numpy as np\n", "from SPCSim.utils.plot_utils import plot_transient, plot_edh\n", "\n", "\n", "seed_val = 43\n", "\n", "# Simulating results for distance = 0.1*dmax\n", "PixLdr = PerPixelLoader(min_dist = 0.32,\n", " tmax = 100,\n", " sig_bkg_list = [\n", " [2,1]],\n", " device = \"cpu\")\n", "\n", "# Generate the per pixel data\n", "data = PixLdr.get_data()\n", "\n", "\n", "# Creating transient generator with laser time period of 100ns, FWHM 1 and with\n", "# laser time period divided into 1000 equal time-bins\n", "tr_gen = TransientGenerator(N_tbins = 1000, tmax = PixLdr.tmax, FWHM = 0.32)\n", "\n", "\n", "# Using the get function to generate the transient\n", "# for a given distance, albedo, intensity, and illumination condition\n", "phi_bar = tr_gen.get_transient(data[\"gt_dist\"],\n", " data[\"albedo\"],\n", " data[\"albedo\"],\n", " data[\"alpha_sig\"],\n", " data[\"alpha_bkg\"])\n", "\n", "\n", "# Setting the dimensions, device, number of EWH bins per pixel\n", "# and number of laser pulses\n", "\n", "Nr, Nc, N_tbins = phi_bar.shape\n", "device = PixLdr.device\n", "N_edhbins = 32\n", "N_pulses = 5000\n", "\n", "# Set row and column of the pixel for which you want to track the CV trajectories\n", "ROW, COL = [0,0]\n", "\n", "spc1 = PEDHOptimized(PixLdr.Nr,\n", " PixLdr.Nc,\n", " N_pulses,\n", " device,\n", " N_tbins,\n", " N_edhbins,\n", " pix_r = ROW,\n", " pix_c = COL,\n", " seed = seed_val,\n", " step_params={\n", " \"k\":3, # Step size gain\n", " \"decay\":0, # Setting decay = 0 allows to update final decay value as a function of N_pulses\n", " \"mtm\":0.8,\n", " \"min_clip\":0.02,\n", " \"switch_fraction\":0.8,\n", " \"delta_mem\": 0.95\n", " })\n", "\n", "\n", "postproc = PostProcEDH(Nr, Nc, N_tbins, PixLdr.tmax, PixLdr.device)\n", "\n", "captured_data = spc1.capture(phi_bar)\n", "edh_data = captured_data[\"edh\"]\n", "\n", "oedh_data = captured_data[\"oedh\"]\n", "\n", "ewh_data = captured_data[\"ewh\"]\n", "\n", "oedh_rho0, _, _, oedh_pred_depth0 = postproc.edh2depth_t(oedh_data[:,:,1:-1], mode=0)\n", "oedh_rho1, _, _, oedh_pred_depth1 = postproc.edh2depth_t(oedh_data[:,:,1:-1], mode=1)\n", "oedh_bin_w_inv_, oedh_bin_idx_, _, oedh_pred_depth = postproc.edh2depth_t(oedh_data[:,:,1:-1], mode=2)\n", "\n", "edh_rho0, _, _, edh_pred_depth0 = postproc.edh2depth_t(edh_data[:,:,1:-1], mode=0)\n", "edh_rho1, _, _, edh_pred_depth1 = postproc.edh2depth_t(edh_data[:,:,1:-1], mode=1)\n", "edh_bin_w_inv_, edh_bin_idx_, _, edh_pred_depth = postproc.edh2depth_t(edh_data[:,:,1:-1], mode=2)\n", "\n", "\n", "fig, (ax, ax2) = plt.subplots(1,2, figsize=(12,4))\n", "\n", "\n", "ymax = ((torch.sum(ewh_data[ROW,COL,:])/N_edhbins)).item()\n", "\n", "\n", "sig, bkg = [data[\"alpha_sig\"][ROW,COL].item(), data[\"alpha_bkg\"][ROW, COL].item()]\n", "\n", "edh_rho0_pix = edh_rho0[ROW, COL, :].cpu().numpy()\n", "edh_rho1_pix = edh_rho1[ROW, COL, :].cpu().numpy()\n", "edh_bin_w_inv_ = edh_bin_w_inv_[ROW, COL, :].cpu().numpy()\n", "edh_bin_idx_ = edh_bin_idx_[ROW, COL, :].cpu().numpy()\n", "\n", "oedh_rho0_pix = oedh_rho0[ROW, COL, :].cpu().numpy()\n", "oedh_rho1_pix = oedh_rho1[ROW, COL, :].cpu().numpy()\n", "oedh_bin_w_inv_ = oedh_bin_w_inv_[ROW, COL, :].cpu().numpy()\n", "oedh_bin_idx_ = oedh_bin_idx_[ROW, COL, :].cpu().numpy()\n", "\n", "tr1 = phi_bar[ROW, COL,:].cpu().numpy()\n", "ax.set_title(\"(a) Oracle EDH\")\n", "plot_transient(ax, oedh_rho0_pix, label=r'$\\rho_0$', plt_type='*-g')\n", "plot_transient(ax, oedh_rho1_pix, label=r'$\\rho_1$', plt_type='*-b')\n", "plot_transient(ax, tr1*oedh_rho0_pix.max()/tr1.max(), label = r'True transient $\\bar\\Phi$', plt_type='-r')\n", "# ax.step(oedh_bin_idx_,oedh_bin_w_inv_,\"o:r\", where=\"pre\", label=\"True data points (step plot used in paper)\")\n", "ax.legend()\n", "ax.set_xlim(left= max(np.argmax(tr1) - 10*tr_gen.smooth_sigma, 0), right = min(np.argmax(tr1) + 10*tr_gen.smooth_sigma, N_tbins))\n", "\n", "ax2.set_title(\"(a) PEDH\")\n", "plot_transient(ax2, edh_rho0_pix, label=r'$\\rho_0$', plt_type='*-g')\n", "plot_transient(ax2, edh_rho1_pix, label=r'$\\rho_1$', plt_type='*-b')\n", "plot_transient(ax2, tr1*edh_rho0_pix.max()/tr1.max(), label = r'True transient $\\bar\\Phi$', plt_type='-r')\n", "# ax.step(edh_bin_idx_,edh_bin_w_inv_,\"o:r\", where=\"pre\", label=\"True data points (step plot used in paper)\")\n", "ax2.legend()\n", "\n", "ax2.set_xlim(left= max(np.argmax(tr1) - 10*tr_gen.smooth_sigma, 0), right = min(np.argmax(tr1) + 10*tr_gen.smooth_sigma, N_tbins))\n", "\n", "handles, labels = ax.get_legend_handles_labels()\n", "fig.legend(handles, labels, loc='lower center', ncol=3, fontsize=\"12\")\n", "plt.xticks(fontsize=12)\n", "plt.yticks(fontsize=12)\n", "fig.savefig(\"Temp_Fig4.png\")\n" ] }, { "cell_type": "markdown", "metadata": { "id": "uwsm9VbM_PJw" }, "source": [ "**********\n", "References\n", "**********\n", "\n", "[1] Sadekar, K., Maier, D., & Ingle, A. (2025). Single-Photon 3D Imaging with Equi-Depth Photon Histograms. In European Conference on Computer Vision (pp. 381-398). Springer, Cham.\n" ] } ], "metadata": { "colab": { "authorship_tag": "ABX9TyMkHtPUB/JRxbu05Oe1LpTj", "mount_file_id": "1-WgmMxjjaewCcarbfvvcjlnS0r3I20di", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "name": "python3" }, "language_info": { "name": "python" } }, "nbformat": 4, "nbformat_minor": 0 }