AI Video2026
Performs task-aware generative video restoration and editing in latent video space — restoration, super-resolution, watermark and subtitle removal — adapting LTX‑2.3 with IC‑Edit/IC‑LoRA adapters to prioritize temporal consistency and occlusion-aware reconstruction.
AI Video2026
Enables Claude to “watch” videos by extracting timestamped frames plus captions/transcripts and feeding them to Claude for grounded Q&A. Key features: native captions first, Whisper fallback, frame deduplication, and multiple detail modes (transcript/efficient/balanced/token-burner). Useful for summarizing, debugging, and extracting moments.
AI Video2026
Cross-platform native video editor with hardware-accelerated processing and frame-accurate multi-track timeline; core editor is open-source and free while optional Pro AI features (natural-language editing, auto-captions, smart reframing) are paid.
AI Model2026
Converts video inputs into text outputs — supports captioning, temporal grounding, and video-text-to-text queries using a Qwen-3.5-2B finetuned multimodal backbone. Suited for prototyping video understanding and caption-generation pipelines.
AI Video2026
Generates minute-scale, 720p videos from a single image using a 2.6B image-to-video diffusion transformer with precise 6‑DoF camera control and an optional LTX‑2 refiner; designed for long-context, memory-efficient modeling but requires large refiner checkpoints (~41 GB).
AI Model2026
Generates temporally coherent MP4 videos from a single input image plus text instructions, with configurable resolution, frame count, and optional AAC audio. Optimized for NVIDIA GPU stacks and integrates with vLLM‑Omni and Hugging Face Diffusers for production inference and research workflows.
AI Video2026
Generates audio-driven avatar videos from text, images, or audio inputs with production-grade stability (accurate lip sync, identity consistency) and an 8-step distillation inference mode for faster serving; suitable for broadcasting, virtual hosts, animation, and multi-person scenarios.
AI Model2026
Performs hour-scale video understanding and fine-grained temporal localization while exposing agent-style multimodal tool/code/search abilities. Built on a sparse-attention long-context architecture (DSA) and a specialized inference stack—best used in GPU-backed research or production evaluation.
AI Video2026
Provides the renderer weights and inference code for Bernini’s video renderer, enabling text→video, image→video and video editing inference. Offers a ready diffusers-format bundle or safetensors checkpoints under Apache‑2.0; intended for multi‑GPU/Hopper inference and reproducible research.
AI Video2026
Generates minute-level, multi-shot synchronized audio+video from a single text prompt, using a paired cross-modal memory to preserve character appearance and voice across shots. Uses DMD-distilled few-step inference for ~7.5× speedup; requires high-GPU memory and is released under the LTX-2 community license.
AI Video2026
End-to-end pose-driven image-to-video model that animates a reference character from a driving video, supporting cross-identity replacement and multi-character scenarios without intermediate pose representations; performs best at 704p and ships as a diffusers-compatible checkpoint.
AI Video2026
Converts low‑poly 3D viewport or game/CG renders into photorealistic cinematic video while preserving the input's composition, camera motion and layout; offers Light and Strong LoRA variants to trade fidelity for aggressive photorealism.