Average Model Cost: $0.0140
Number of Runs: 466,095
Models by this creator
ModNet is a deep learning model that enables the removal of background from an image and the addition of a new background. It uses a background matting technique to accurately segment the foreground and background. By training on large datasets, the model learns to accurately predict the alpha matte, which represents the opacity of each pixel, and the foreground. This allows for precise removal of the background and seamless replacement with a new background image. ModNet is a powerful tool for various image editing applications and can be used to create visually appealing compositions or remove unwanted elements from images.
Audiocraft is a library that specializes in audio processing and generation using deep learning techniques. It allows researchers and developers to work with audio data and apply machine learning algorithms to tasks such as music generation. The library provides tools and techniques for processing and manipulating audio signals, as well as generating new audio samples based on given inputs. It is designed to support the development of models and systems for various audio-related applications.
The RealBasicVSR model is a video super-resolution architecture that focuses on real-world scenarios. It aims to enhance the quality of low-resolution videos by generating high-resolution frames. The model considers tradeoffs such as computational efficiency and perceptual quality to achieve optimal performance. This research investigates different aspects of real-world video super-resolution and provides insights into the tradeoffs involved.
Adampi is a model that takes single 2D images and generates 3D photos. It is designed for images captured in real-world conditions and uses a deep learning algorithm to convert the 2D image into a 3D representation. This model can be useful in various applications such as virtual reality, augmented reality, and 3D reconstruction.
The 3d-photo-inpainting model is an image-to-image conversion model that takes as input a 2D image with depth map information and generates a 3D photo representation of the scene. It uses a context-aware layered depth inpainting technique to fill in the missing depth information and generate a realistic 3D photo. This model can be useful in various applications such as virtual reality, augmented reality, and 3D visualization.
The stable-diffusion-dance model is a text-to-video model that takes in audio input and generates a video output in response. It uses stable diffusion, a technique for synthesizing video frames based on a set of input keyframes, to create a visually appealing dance animation that is synchronized with the audio. The model combines the audio features with a pre-trained visual backbone to generate hallucination frames that are then stabilized to produce the final video output. This model can be used in various applications such as music visualization, artistic expression, and entertainment.
Lucid Sonic Dreams is a model that utilizes a Generative Adversarial Network (GAN) to generate visuals that are synchronized with music. It takes an input of audio and generates corresponding video frames to create an immersive audio-visual experience. This model allows for the creation of dynamic and visually engaging content by automatically generating visuals that complement the audio.
Tune-a-Video is a model designed for text-to-video generation. It focuses on tuning image diffusion models to generate high-quality videos based on text inputs. The model uses a one-shot tuning approach, which means that it only requires a single training iteration to achieve the desired video generation results. This makes it faster and more efficient compared to traditional approaches that require multiple iterations. By optimizing the diffusion model, Tune-a-Video produces better visual quality and more accurate video generation from textual descriptions.
Lucid Sonic Dreams XL is a model that combines StyleGAN XL-generated visuals with music. It synchronizes the generated visuals to the music to create a visually immersive experience. This model allows users to create audio-to-video visuals that are visually appealing and synchronized with the music being played.