diff --git a/scenedetect/detectors/adaptive_detector.py b/scenedetect/detectors/adaptive_detector.py
index 2e98bbf4..8f3f5800 100644
--- a/scenedetect/detectors/adaptive_detector.py
+++ b/scenedetect/detectors/adaptive_detector.py
@@ -136,7 +136,8 @@ def process_frame(self, timecode: FrameTimecode, frame_img: np.ndarray) -> list[
         threshold_met: bool = (
             adaptive_ratio >= self.adaptive_threshold and target_score >= self.min_content_val
         )
-        min_length_met: bool = (timecode - self._last_cut) >= self.min_scene_len
+        # Cuts are emitted at `target_timecode` (`window_width` behind `timecode`).
+        min_length_met: bool = (target_timecode - self._last_cut) >= self.min_scene_len
         if threshold_met and min_length_met:
             self._last_cut = target_timecode
             return [target_timecode]
diff --git a/tests/test_detectors.py b/tests/test_detectors.py
index a6a9f283..6754d910 100644
--- a/tests/test_detectors.py
+++ b/tests/test_detectors.py
@@ -19,6 +19,7 @@
 import os
 from dataclasses import dataclass
 
+import numpy as np
 import pytest
 
 from scenedetect import FrameTimecode, SceneDetector, SceneManager, StatsManager, detect
@@ -261,3 +262,33 @@ def test_min_scene_len_accepts_time_values(detector_type, min_scene_len):
     scene_list = test_case.detect()
     start_frames = [timecode.frame_num for timecode, _ in scene_list]
     assert start_frames == test_case.scene_boundaries
+
+
+def test_adaptive_detector_min_scene_len_uses_target_frame():
+    """AdaptiveDetector applies min_scene_len to the emitted cut, not the current frame.
+
+    AdaptiveDetector scores a target frame `window_width` behind the frame currently
+    being processed. Comparing min_scene_len against the current frame lets a second
+    peak emit a cut only `window_width` frames after the previous one (issue #408).
+    """
+    window_width = 20
+    min_scene_len = 24
+    detector = AdaptiveDetector(
+        adaptive_threshold=2.0,
+        window_width=window_width,
+        min_scene_len=min_scene_len,
+        min_content_val=15.0,
+        luma_only=True,
+    )
+    fps = 30.0
+    n_frames = 180
+    cuts: list[FrameTimecode] = []
+    for frame_num in range(n_frames):
+        # Hard cuts at 100 and 104 (4 frames apart) plus a later valid cut at 140.
+        # The 4-frame pair matches the report: min_scene_len - window_width.
+        value = 255 if 100 <= frame_num <= 103 or 140 <= frame_num <= 143 else 0
+        frame = np.full((16, 16, 3), value, dtype=np.uint8)
+        cuts.extend(detector.process_frame(FrameTimecode(frame_num, fps), frame))
+
+    cut_frames = [cut.frame_num for cut in cuts]
+    assert cut_frames == [100, 140]
diff --git a/website/pages/changelog.md b/website/pages/changelog.md
index 7789e5c8..1cf9920a 100644
--- a/website/pages/changelog.md
+++ b/website/pages/changelog.md
@@ -782,6 +782,7 @@ Development
 
 ## PySceneDetect 0.7.2 (TBD)
 
+ - [bugfix] Fix `AdaptiveDetector` / `detect-adaptive` emitting scenes shorter than `min_scene_len` when `window_width` is large, by applying the minimum-length check to the emitted (target) frame instead of the current frame [#408](https://github.com/Breakthrough/PySceneDetect/issues/408)
  - [general] The `scenedetect-core` package introduced in 0.7.1 has been discontinued, and its only release (0.7.1) yanked from PyPI: pip cannot safely support multiple packages that install the same module files, and restructuring the existing packages around a shared core would break in-place upgrades. Existing `scenedetect-core` installs keep working but will not receive updates; continue to install `scenedetect` or `scenedetect-headless` as usual.
  - [improvement] `HistogramDetector` (`detect-hist`) default `threshold` changed from 0.05 to 0.20 and default `bins` from 256 to 128, calibrated from the [benchmark sweep](https://www.scenedetect.com/benchmarks/) for significantly better accuracy. Default output for this detector will change [#559](https://github.com/Breakthrough/PySceneDetect/issues/559)
  - [improvement] `HashDetector` (`detect-hash`) default `threshold` changed from 0.395 to 0.35 and default `size` from 16 to 8, calibrated from the [benchmark sweep](https://www.scenedetect.com/benchmarks/) for better accuracy. Default output for this detector will change, including the statsfile metric key (now `hash_dist [size=8 lowpass=2]`) [#559](https://github.com/Breakthrough/PySceneDetect/issues/559)