[HN Gopher] YOLO-World: Real-Time Open-Vocabulary Object Detection
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       YOLO-World: Real-Time Open-Vocabulary Object Detection
        
       Author : greesil
       Score  : 52 points
       Date   : 2025-05-31 20:54 UTC (2 hours ago)
        
 (HTM) web link (arxiv.org)
 (TXT) w3m dump (arxiv.org)
        
       | ed wrote:
       | Neat. Wonder how this compares to Segment Anything (SAM), which
       | also does zero-shot segmentation and performs pretty well in my
       | experience.
        
         | ipsum2 wrote:
         | SAM doesn't do open vocabulary i.e. it segments things without
         | knowing the name of the object, so you can't ask it to do
         | "highlight the grapes", you have to give it an example of a
         | grape first.
        
           | stevepotter wrote:
           | Try this: https://github.com/luca-medeiros/lang-segment-
           | anything
        
             | ipsum2 wrote:
             | This uses GroundingDINO for open vocabulary, separate
             | model. Useful nonetheless, but means you're running a lot
             | of model inference for a single image.
        
         | RugnirViking wrote:
         | YOLO is way faster. We used to run both, with YOLO finding
         | candidate bounding boxes and SAM segmenting just those.
         | 
         | For what it's worth, YOLO has been a standard in image
         | processing for ages at this point, with dozens of variations on
         | the algorithm (yolov3, yolov5, yolov6, etc) and this is yet
         | another new one. Looks great tho
         | 
         | SAM wouldn't run under 1000ms per frame for most reasonable
         | image sizes
        
       | AndrewKemendo wrote:
       | We've tested this in our production environment on mobile robots
       | (think quadcopter and ground UGV) and it works really nicely
        
         | TechDebtDevin wrote:
         | If this is military related, im terrified of the future. Sci-fi
         | movies with crazy drones from back when are no longer that
         | cute.
        
           | jiggawatts wrote:
           | The truly scary part is that it's a straightforward evolution
           | from this to 1000 fps hyperspectral sensors.
           | 
           | There will be no hiding from these things and no possibility
           | of evasion.
           | 
           | They'll have agility exceeding champion drone pilots and be
           | too small to even see or hear until it's far too late.
           | 
           | Life in the Donbass trenches is already hell. We'll find a
           | way to make it worse.
        
         | bevenky wrote:
         | Is this OSS?
        
           | T-A wrote:
           | https://github.com/AILab-CVC/YOLO-World
        
           | fc417fc802 wrote:
           | Unclear exactly what you're asking. The linked paper
           | describes an algorithm (patent status unclear). That paper
           | happens to link to a GPL licensed implementation whose
           | authors explicitly solicit business licensing inquiries. The
           | related model weights are available on Hugging Face (license
           | unclear). Notably the HF readme file contains conflicting
           | claims. The metadata specifies apache while the body
           | specifies GPL.
           | 
           | https://github.com/AILab-CVC/YOLO-World
           | 
           | https://huggingface.co/spaces/stevengrove/YOLO-
           | World/tree/ma...
        
       | silentsea90 wrote:
       | Q. Any of you know models that do well at deleting objects from
       | an image i.e. inpainting with mask with intention to replace mask
       | with background? Whatever I've tried so far leaves a smudge (eg.
       | LaMa)
        
         | GaggiX wrote:
         | There are plenty of Stable Diffusion based models that are
         | capable of inpainting, of course they are heavier to run than
         | LaMa.
        
       | pavl wrote:
       | This looks so good! Will it be available on replicate?
        
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       (page generated 2025-05-31 23:00 UTC)