diff --git a/modules/dnn/src/graph_fusion_qdq.cpp b/modules/dnn/src/graph_fusion_qdq.cpp
index 4ac53fdefa..7ef3da8113 100644
--- a/modules/dnn/src/graph_fusion_qdq.cpp
+++ b/modules/dnn/src/graph_fusion_qdq.cpp
@@ -486,7 +486,16 @@ struct ModelFusionQDQ
                                         symmetric_pads = false;
                                 }
 
-                                if (all_wzp_zero && symmetric_pads) {
+                                // Conv2Int8's VNNI kernel processes K0=8 output channels per
+                                // SIMD iteration. When ngroups>1 and Kg<K0, multiple groups map
+                                // to the same K0-wide output slot and clobber one another, so
+                                // skip the fusion and fall back to the unfused float path.
+                                // See https://github.com/opencv/opencv/issues/28798
+                                const int outChannelsPerGroup = outCn / std::max(conv->ngroups, 1);
+                                const bool kernelSupportsGrouping =
+                                    conv->ngroups <= 1 || outChannelsPerGroup >= 8;
+
+                                if (all_wzp_zero && symmetric_pads && kernelSupportsGrouping) {
                                     Mat bias = Mat::zeros(1, outCn, CV_32S);
                                     bool biasOk = true;
                                     int dq_bias_idx = -1;
diff --git a/modules/dnn/test/test_onnx_importer.cpp b/modules/dnn/test/test_onnx_importer.cpp
index a6ee94f5b0..d43fe21717 100644
--- a/modules/dnn/test/test_onnx_importer.cpp
+++ b/modules/dnn/test/test_onnx_importer.cpp
@@ -2197,6 +2197,11 @@ TEST_P(Test_ONNX_layers, Quantized_Convolution)
         testONNXModels("quantized_conv_int8_weights", npy, 0.03, 0.5);
         testONNXModels("quantized_conv_per_channel_weights", npy, 0.06, 0.4);
         testONNXModels("quantized_conv_asymmetric_pads_int8_weights");
+        // Regression test for https://github.com/opencv/opencv/issues/28798:
+        // depthwise QLinearConv (Kg=1 < kernel SIMD width K0=8) used to be
+        // miscompiled by Conv2Int8's VNNI kernel because multiple groups
+        // wrote into the same K0-wide output slot.
+        testONNXModels("quantized_depthwise_conv_int8_weights", npy, 0.06, 0.5);
     }
 
     {
diff --git a/samples/dnn/face_detect.cpp b/samples/dnn/face_detect.cpp
index 1f9e6a0ae0..b8c3b622e6 100644
--- a/samples/dnn/face_detect.cpp
+++ b/samples/dnn/face_detect.cpp
@@ -46,7 +46,7 @@ int main(int argc, char** argv)
         "{scale sc          | 1.0        | Scale factor used to resize input video frames}"
         "{fd_model fd       | face_detection_yunet_2023mar.onnx| Path to the model. Download yunet.onnx in https://github.com/opencv/opencv_zoo/tree/master/models/face_detection_yunet}"
         "{fr_model fr       | face_recognition_sface_2021dec.onnx | Path to the face recognition model. Download the model at https://github.com/opencv/opencv_zoo/tree/master/models/face_recognition_sface}"
-        "{score_threshold   | 0.9        | Filter out faces of score < score_threshold}"
+        "{score_threshold   | 0.85       | Filter out faces of score < score_threshold}"
         "{nms_threshold     | 0.3        | Suppress bounding boxes of iou >= nms_threshold}"
         "{top_k             | 5000       | Keep top_k bounding boxes before NMS}"
         "{save s            | false      | Set true to save results. This flag is invalid when using camera}"
diff --git a/samples/dnn/face_detect.py b/samples/dnn/face_detect.py
index f07c5f3be1..95012fdbba 100644
--- a/samples/dnn/face_detect.py
+++ b/samples/dnn/face_detect.py
@@ -18,7 +18,7 @@ parser.add_argument('--video', '-v', type=str, help='Path to the input video.')
 parser.add_argument('--scale', '-sc', type=float, default=1.0, help='Scale factor used to resize input video frames.')
 parser.add_argument('--face_detection_model', '-fd', type=str, default='face_detection_yunet_2023mar.onnx', help='Path to the face detection model. Download the model at https://github.com/opencv/opencv_zoo/tree/master/models/face_detection_yunet')
 parser.add_argument('--face_recognition_model', '-fr', type=str, default='face_recognition_sface_2021dec.onnx', help='Path to the face recognition model. Download the model at https://github.com/opencv/opencv_zoo/tree/master/models/face_recognition_sface')
-parser.add_argument('--score_threshold', type=float, default=0.9, help='Filtering out faces of score < score_threshold.')
+parser.add_argument('--score_threshold', type=float, default=0.85, help='Filtering out faces of score < score_threshold.')
 parser.add_argument('--nms_threshold', type=float, default=0.3, help='Suppress bounding boxes of iou >= nms_threshold.')
 parser.add_argument('--top_k', type=int, default=5000, help='Keep top_k bounding boxes before NMS.')
 parser.add_argument('--save', '-s', type=str2bool, default=False, help='Set true to save results. This flag is invalid when using camera.')