diff --git a/CMakeLists.txt b/CMakeLists.txt
index 1ae4289..0e75e3b 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -159,6 +159,9 @@ target_link_libraries(map_demo tkDNN)
 add_executable(demo demo/demo/demo.cpp)
 target_link_libraries(demo tkDNN)
 
+add_executable(demo3D demo/demo/demo3D.cpp)
+target_link_libraries(demo3D tkDNN)
+
 #-------------------------------------------------------------------------------
 # Install
 #-------------------------------------------------------------------------------
diff --git a/demo/demo/demo3D.cpp b/demo/demo/demo3D.cpp
new file mode 100644
index 0000000..e838395
--- /dev/null
+++ b/demo/demo/demo3D.cpp
@@ -0,0 +1,103 @@
+#include <iostream>
+#include <signal.h>
+#include <stdlib.h>     /* srand, rand */
+#include <unistd.h>
+#include <mutex>
+
+#include "CenternetDetection3D.h"
+
+bool gRun;
+bool SAVE_RESULT = false;
+
+void sig_handler(int signo) {
+    std::cout<<"request gateway stop\n";
+    gRun = false;
+}
+
+int main(int argc, char *argv[]) {
+
+    std::cout<<"detection\n";
+    signal(SIGINT, sig_handler);
+
+
+    std::string net = "dla34_cnet3d_fp32.rt";
+    if(argc > 1)
+        net = argv[1]; 
+    std::string input = "../demo/yolo_test.mp4";
+    if(argc > 2)
+        input = argv[2]; 
+    char ntype = 'c';
+    if(argc > 3)
+        ntype = argv[3][0]; 
+    int n_classes = 3;
+    if(argc > 4)
+        n_classes = atoi(argv[4]); 
+
+    tk::dnn::CenternetDetection3D cnet;
+
+    tk::dnn::DetectionNN3D *detNN;  
+
+    switch(ntype)
+    {
+        case 'c':
+            detNN = &cnet;
+            break;
+        default:
+        FatalError("Network type not allowed (3rd parameter)\n");
+    }
+
+    detNN->init(net, n_classes);
+
+    gRun = true;
+
+    cv::VideoCapture cap(input);
+    if(!cap.isOpened())
+        gRun = false; 
+    else
+        std::cout<<"camera started\n";
+
+    cv::VideoWriter resultVideo;
+    if(SAVE_RESULT) {
+        int w = cap.get(cv::CAP_PROP_FRAME_WIDTH);
+        int h = cap.get(cv::CAP_PROP_FRAME_HEIGHT);
+        resultVideo.open("result.mp4", cv::VideoWriter::fourcc('M','P','4','V'), 30, cv::Size(w, h));
+    }
+
+    cv::Mat frame;
+    cv::Mat dnn_input;
+    cv::namedWindow("detection", cv::WINDOW_NORMAL);
+    
+    std::vector<tk::dnn::box> detected_bbox;
+
+    while(gRun) {
+        cap >> frame; 
+        if(!frame.data) {
+            break;
+        }  
+ 
+        // this will be resized to the net format
+        dnn_input = frame.clone();
+        
+        //inference
+        detNN->update(dnn_input);
+        frame = detNN->draw(frame);
+
+        cv::imshow("detection", frame);
+        cv::waitKey(1);
+        if(SAVE_RESULT)
+            resultVideo << frame;
+    }
+
+    std::cout<<"detection end\n";   
+    double mean = 0; 
+    
+    std::cout<<COL_GREENB<<"\n\nTime stats:\n";
+    std::cout<<"Min: "<<*std::min_element(detNN->stats.begin(), detNN->stats.end())<<" ms\n";    
+    std::cout<<"Max: "<<*std::max_element(detNN->stats.begin(), detNN->stats.end())<<" ms\n";    
+    for(int i=0; i<detNN->stats.size(); i++) mean += detNN->stats[i]; mean /= detNN->stats.size();
+    std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;   
+    
+
+    return 0;
+}
+