Beeble Background Remover vs Robust Video Matting
Beeble Background Remover
beeble.aiRobust Video Matting
github.comSide by side
| Figure | Beeble Background Remover | Robust Video Matting |
|---|---|---|
| Price from | $16/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Linux | — | Yes |
| iOS | Yes | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 5 | 1 |
| Spec score · AI Video Background Removers | 9.2 (#4) | 8.2 (#13) |
| Purpose | Background Remover creates an alpha matte from images, videos, or image sequences, without requiring a green screen. | Robust Video Matting is designed for human video matting and uses a recurrent neural network with temporal memory to process video frames. |
Plans
Beeble Background Remover
- FreeFree
- Creator$16 a month
- Creator$16 a month
- Professional$60 a month
- Professional$60 a month
In their own words
Beeble Background Remover
Beeble Background Remover has no write-up on Specifiction yet; its figures are above.
Robust Video Matting
Robust Video Matting is a free project for separating people from video backgrounds. It processes frames with a recurrent neural network that carries temporal memory, and the project says it can perform matting in real time without additional inputs. A browser webcam demo runs the model live and can visualize its recurrent states. The conversion API accepts a video or image sequence and can produce a composited video or PNG sequence, optionally including alpha and foreground outputs.
Models are available for PyTorch, TorchHub, TorchScript, ONNX, TensorFlow, TensorFlow.js, and CoreML. MobileNetv3 is recommended for most uses; ResNet50 is larger and described as offering small performance improvements. The README reports GPU throughput figures, including 4K at 76 FPS and HD at 104 FPS on a GTX 1080 Ti, and 4K at 154 FPS and HD at 172 FPS on an RTX 3090 with FP16 under specified settings. The project cautions that file conversion runs much slower because its script does not use hardware video encoding or decoding or parallel tensor transfers. CoreML models require iOS 13 or later and do not support dynamic resolution. The code is GPL-3.0 licensed.