diff --git a/test/assets/interlaced_png/wizard_low-interlaced.png b/test/assets/interlaced_png/wizard_low-interlaced.png
new file mode 100644
index 00000000000..3badd9264dc
Binary files /dev/null and b/test/assets/interlaced_png/wizard_low-interlaced.png differ
diff --git a/test/assets/interlaced_png/wizard_low.png b/test/assets/interlaced_png/wizard_low.png
new file mode 100644
index 00000000000..7b1c264f030
Binary files /dev/null and b/test/assets/interlaced_png/wizard_low.png differ
diff --git a/test/test_image.py b/test/test_image.py
index 47023a45be2..7c6764dce64 100644
--- a/test/test_image.py
+++ b/test/test_image.py
@@ -20,6 +20,7 @@
 IMAGE_DIR = os.path.join(FAKEDATA_DIR, "imagefolder")
 DAMAGED_JPEG = os.path.join(IMAGE_ROOT, 'damaged_jpeg')
 ENCODE_JPEG = os.path.join(IMAGE_ROOT, "encode_jpeg")
+INTERLACED_PNG = os.path.join(IMAGE_ROOT, "interlaced_png")
 IS_WINDOWS = sys.platform in ('win32', 'cygwin')
 PILLOW_VERSION = tuple(int(x) for x in PILLOW_VERSION.split('.'))
 
@@ -304,6 +305,15 @@ def test_read_1_bit_png_consistency(shape, mode):
         assert_equal(img1, img2)
 
 
+def test_read_interlaced_png():
+    imgs = list(get_images(INTERLACED_PNG, ".png"))
+    with Image.open(imgs[0]) as im1, Image.open(imgs[1]) as im2:
+        assert not (im1.info.get("interlace") is im2.info.get("interlace"))
+    img1 = read_image(imgs[0])
+    img2 = read_image(imgs[1])
+    assert_equal(img1, img2)
+
+
 @needs_cuda
 @pytest.mark.parametrize('img_path', [
     pytest.param(jpeg_path, id=_get_safe_image_name(jpeg_path))
diff --git a/torchvision/csrc/io/image/cpu/decode_png.cpp b/torchvision/csrc/io/image/cpu/decode_png.cpp
index b40fd951d5b..ea38272c978 100644
--- a/torchvision/csrc/io/image/cpu/decode_png.cpp
+++ b/torchvision/csrc/io/image/cpu/decode_png.cpp
@@ -55,6 +55,7 @@ torch::Tensor decode_png(const torch::Tensor& data, ImageReadMode mode) {
 
   png_uint_32 width, height;
   int bit_depth, color_type;
+  int interlace_type;
   auto retval = png_get_IHDR(
       png_ptr,
       info_ptr,
@@ -62,7 +63,7 @@ torch::Tensor decode_png(const torch::Tensor& data, ImageReadMode mode) {
       &height,
       &bit_depth,
       &color_type,
-      nullptr,
+      &interlace_type,
       nullptr,
       nullptr);
 
@@ -81,6 +82,13 @@ torch::Tensor decode_png(const torch::Tensor& data, ImageReadMode mode) {
   if (color_type == PNG_COLOR_TYPE_GRAY && bit_depth < 8)
     png_set_expand_gray_1_2_4_to_8(png_ptr);
 
+  int number_of_passes;
+  if (interlace_type == PNG_INTERLACE_ADAM7) {
+    number_of_passes = png_set_interlace_handling(png_ptr);
+  } else {
+    number_of_passes = 1;
+  }
+
   if (mode != IMAGE_READ_MODE_UNCHANGED) {
     // TODO: consider supporting PNG_INFO_tRNS
     bool is_palette = (color_type & PNG_COLOR_MASK_PALETTE) != 0;
@@ -163,9 +171,12 @@ torch::Tensor decode_png(const torch::Tensor& data, ImageReadMode mode) {
   auto tensor =
       torch::empty({int64_t(height), int64_t(width), channels}, torch::kU8);
   auto ptr = tensor.accessor<uint8_t, 3>().data();
-  for (png_uint_32 i = 0; i < height; ++i) {
-    png_read_row(png_ptr, ptr, nullptr);
-    ptr += width * channels;
+  for (int pass = 0; pass < number_of_passes; pass++) {
+    for (png_uint_32 i = 0; i < height; ++i) {
+      png_read_row(png_ptr, ptr, nullptr);
+      ptr += width * channels;
+    }
+    ptr = tensor.accessor<uint8_t, 3>().data();
   }
   png_destroy_read_struct(&png_ptr, &info_ptr, nullptr);
   return tensor.permute({2, 0, 1});