diff --git a/ptflops/pytorch_ops.py b/ptflops/pytorch_ops.py
index d6e535a..7fe061a 100644
--- a/ptflops/pytorch_ops.py
+++ b/ptflops/pytorch_ops.py
@@ -6,6 +6,8 @@
  * this file. If not visit https://opensource.org/licenses/MIT
 '''
 
+from functools import partial
+
 import numpy as np
 import torch
 import torch.nn as nn
@@ -55,12 +57,11 @@ def bn_flops_counter_hook(module, input, output):
     module.__flops__ += int(batch_flops)
 
 
-def conv_flops_counter_hook(conv_module, input, output, extra_per_position_flops=0):
+def conv_flops_counter_hook(conv_module, input, output, extra_per_position_flops=0, transpose=False):
     # Can have multiple inputs, getting the first one
     input = input[0]
 
     batch_size = input.shape[0]
-    output_dims = list(output.shape[2:])
 
     kernel_dims = list(conv_module.kernel_size)
     in_channels = conv_module.in_channels
@@ -71,7 +72,12 @@ def conv_flops_counter_hook(conv_module, input, output, extra_per_position_flops
     conv_per_position_flops = int(np.prod(kernel_dims, dtype=np.int64)) * \
         (in_channels * filters_per_channel + extra_per_position_flops)
 
-    active_elements_count = batch_size * int(np.prod(output_dims, dtype=np.int64))
+    if transpose:
+        input_dims = list(input.shape[2:])
+        active_elements_count = batch_size * int(np.prod(input_dims, dtype=np.int64))
+    else:
+        output_dims = list(output.shape[2:])
+        active_elements_count = batch_size * int(np.prod(output_dims, dtype=np.int64))
 
     overall_conv_flops = conv_per_position_flops * active_elements_count
 
@@ -301,9 +307,9 @@ def timm_attention_counter_hook(attention_module, input, output):
     # Upscale
     nn.Upsample: upsample_flops_counter_hook,
     # Deconvolution
-    nn.ConvTranspose1d: conv_flops_counter_hook,
-    nn.ConvTranspose2d: conv_flops_counter_hook,
-    nn.ConvTranspose3d: conv_flops_counter_hook,
+    nn.ConvTranspose1d: partial(conv_flops_counter_hook, transpose=True),
+    nn.ConvTranspose2d: partial(conv_flops_counter_hook, transpose=True),
+    nn.ConvTranspose3d: partial(conv_flops_counter_hook, transpose=True),
     # RNN
     nn.RNN: rnn_flops_counter_hook,
     nn.GRU: rnn_flops_counter_hook,