Based on BFS - Best Face Swap, VisoMaster, and SwapAnyHead.
Radar
New projects people are discovering or following across Pinokio.
a state-of-the-art open-source model for fast feedforward 3D reconstruction from a single image, developed in collaboration between Tripo AI and Stability AI. https://huggingface.co/spaces/stabilityai/TripoSR
Differential Diffusion modifies an image according to a text prompt, and according to a map that specifies the amount of change in each region https://differential-diffusion.github.io/
A unified image generation model that you can use to perform various tasks, including but not limited to text-to-image generation, subject-driven generation, Identity-Preserving Generation, and image-conditioned generation. https://huggingface.co/spaces/Shitao/OmniGen
Face swapping for images and video, with a React UI. Independent project; AGPL-3.0. Private — access is by invitation.
Estúdio IA para Criação de Letras, Estruturação de Prompts Suno/Udio/Mureka e Geração Musical YuE2 com Transcrição de Covers SheetSage2.
Browse, preview and compare Wan2GP / WanGP video generations side by side, with the embedded generation settings and a diff of what changed between runs.
AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait Animation:https://github.com/Zejun-Yang/AniPortrait
Super Optimized Gradio UI for AI video creation for GPU poor machines (6GB+ VRAM). Supports Wan 2.1/2.2, Qwen, Hunyuan Video, LTX Video and Flux. https://github.com/deepbeepmeep/Wan2GP
Lightricks LTX-2.3 video generation (22B distilled-1.1) with a Gradio UI. Auto-detects GPU and configures offload.
YUE2 // GROOVE is the latest music studio built on the open-source Yue2 model and its inference stack. Generate high-quality full songs from style and lyrics with an editable score plan — powered by the latest YuE model — cover from audio with SheetSage2 and MERT2, refine and compare edits, and keep your works in a reusable, easy-to-manage library. You get high-quality creation with real creative control. Hardware: an NVIDIA GPU with 24 GB VRAM on Linux (YuE2's recommended setup, validated end-to-end on NVIDIA L4 hosts; a 16 GB memory budget runs everything the app can produce, and 12 GB runs the unquantized model at CFG 1.0 or for shorter songs) or an Apple Silicon Mac with 32 GB+ unified memory (where this app is developed and tested). Windows is best effort: install, launch, Cover and a full-length song verified on Windows 11 (RTX 2070, 8 GB); song generation there runs through the GGUF engine. Cards under 16 GB (and Windows) get the optional GGUF engine: the same model through yue2.cpp with an 8-bit backbone, 8.2 GB peak for a full song, measured indistinguishable from the reference rendering in a blind ABX, a different take for the same seed; the reference PyTorch configuration stays the default wherever it fits.
