Remove the Kling AI Watermark From Video
Kling AI stamps generated videos with its logo, most visible on free-tier exports where the watermark is the trade-off for not paying. It's normally a corner mark held in place through the clip. WatermarkRemoverAI inpaints the Kling logo out of each frame, rebuilding the corner from surrounding footage — a practical cleanup for creators finishing Kling clips they generated themselves.
How to remove the Kling AI watermark
Upload the Kling export
Add the generated MP4. Find the Kling logo — usually pinned in a corner for the whole clip.
Brush the logo
Mask the Kling watermark tightly. Its fixed position means the AI has steady surroundings to reconstruct from frame to frame.
Download the clean clip
Export at Kling's original resolution and frame rate, watermark-free.
Frequently Asked Questions
Why does my Kling video have a watermark?
Kling adds its logo to exports, most prominently on the free tier where the watermark is the cost of free generation. Paid tiers may reduce or remove it; this tool cleans exports that already carry the mark.
Where does the Kling watermark sit?
Typically a fixed corner logo that stays in one position through the clip. A snug mask on that corner, applied across the frames, reconstructs the area cleanly.
Will the removed corner match the AI-generated background?
Kling's synthetic backgrounds are often smooth, which helps the inpainter blend the rebuilt corner in. Highly detailed or fast-moving backgrounds behind the logo are the harder cases.
Does this work on Kling image outputs too?
Yes. Upload a still as an image and remove the corner logo in a single pass — no per-frame processing needed for a photo.
Is it fine to remove the Kling watermark?
Use it on content you generated yourself. Platforms may still ask that AI-generated video be disclosed; removing the visible logo doesn't change the clip's AI origin.
Related Guides
Automate it with the API
Send a file, get a job id back, poll for the clean result. Same AI engine as the web tool, in two requests.
curl -X POST https://api.watermarkremoverai.com/v1/watermark/remove-video/ \
-H "Authorization: YOUR_API_TOKEN" \
-F "files=@video.mp4" \
-F "auto_detect=true"
# => {"uuid": "..."}
# Poll for the result
curl -X POST https://api.watermarkremoverai.com/v1/watermark/results/ \
-d "uuid=..."
import requests
API = "https://api.watermarkremoverai.com/v1/watermark"
headers = {"Authorization": "YOUR_API_TOKEN"}
with open("video.mp4", "rb") as f:
job = requests.post(API + "/remove-video/",
headers=headers,
files={"files": f},
data={"auto_detect": "true"}).json()
result = requests.post(API + "/results/",
data={"uuid": job["uuid"]}).json()
print(result)
Prefer a manual mask? Send mask=@mask.png instead of auto_detect, or pass mask_x / mask_y / mask_width / mask_height (add mask_is_percentage=true for percentages). Optional dilation=5 grows the masked area.
Ready to clean it up?
Upload, mark the area, and download the clean result. No account needed to try it free.
Open the Tool