diff --git a/pcdet/models/detectors/pillarnet.py b/pcdet/models/detectors/pillarnet.py
new file mode 100644
index 0000000..965a441
--- /dev/null
+++ b/pcdet/models/detectors/pillarnet.py
@@ -0,0 +1,50 @@
+from .detector3d_template import Detector3DTemplate
+
+
+class PillarNet(Detector3DTemplate):
+    def __init__(self, model_cfg, num_class, dataset):
+        super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
+        self.module_list = self.build_networks()
+
+    def forward(self, batch_dict):
+        for cur_module in self.module_list:
+            batch_dict = cur_module(batch_dict)
+
+        if self.training:
+            loss, tb_dict, disp_dict = self.get_training_loss()
+
+            ret_dict = {
+                'loss': loss
+            }
+            return ret_dict, tb_dict, disp_dict
+        else:
+            pred_dicts, recall_dicts = self.post_processing(batch_dict)
+            return pred_dicts, recall_dicts
+
+    def get_training_loss(self):
+        disp_dict = {}
+
+        loss_rpn, tb_dict = self.dense_head.get_loss()
+        tb_dict = {
+            'loss_rpn': loss_rpn.item(),
+            **tb_dict
+        }
+
+        loss = loss_rpn
+        return loss, tb_dict, disp_dict
+
+    def post_processing(self, batch_dict):
+        post_process_cfg = self.model_cfg.POST_PROCESSING
+        batch_size = batch_dict['batch_size']
+        final_pred_dict = batch_dict['final_box_dicts']
+        recall_dict = {}
+        for index in range(batch_size):
+            pred_boxes = final_pred_dict[index]['pred_boxes']
+
+            recall_dict = self.generate_recall_record(
+                box_preds=pred_boxes,
+                recall_dict=recall_dict, batch_index=index, data_dict=batch_dict,
+                thresh_list=post_process_cfg.RECALL_THRESH_LIST
+            )
+
+        return final_pred_dict, recall_dict
\ No newline at end of file