Provides an annotated multimodal human-motion dataset for language-to-action and robotics research, with BVH and MuJoCo files plus recordings targeted at Unitree-G1 and NVIDIA-SOMA platforms. Covers locomotion, gestures, dance and object interaction with English annotations and 100K–1M samples.
Generate text, images, video, audio and action/robot trajectories from combined text, image, video, audio and action inputs. A Mixture-of-Transformers omnimodal foundation model (Cosmos3‑Nano, 16B params) focused on Physical AI (robotics, AV, simulation) and optimized for NVIDIA GPU runtimes.
Large-scale mid-training corpora for multimodal models: 10,809 ~60s video shards, caption splits (30s/60s/180s/>10min), 84 spatial-reasoning shards, and CSV mappings to source YouTube IDs. Small Parquet preview configs are provided for schema inspection.
Orchestrates end-to-end video production with agentic pipelines that research, script, generate assets, edit, and render finished videos. Distinguishes itself by supporting true real-footage retrieval (Archive.org, NASA, Wikimedia), Remotion/HyperFrames composition, and usable zero-key workflows alongside cloud providers.
Provides a diagnostic suite that audits video-understanding benchmarks to find samples solvable without visual or temporal input, filters those shortcuts, and produces a distilled video-native testbed that reveals major capability gaps in current Video-LLMs.
Provides curated short video clips (49- and 81-frame) with layered ground truth—edit layers, alpha mattes, and composite targets—for training and evaluating content-preserving layered diffusion video editing. Contains background-replace and object-add edits; Apache-2.0 licensed.
Generative-AI-enabled timeline video editor for macOS that lets creators generate and edit videos and images directly inside the timeline. Includes a local MCP server for agent integrations (Claude/Codex/Cursor); editor is open-source while generative processing is closed-source and subscription-based; macOS 26 on Apple Silicon only.
Automates video editing driven by LLM agents: reads word-level transcripts to propose and execute cuts, remove filler words, auto grade color, burn subtitles, and generate animation overlays. Self-evaluates every cut before showing a preview; aimed at talking-heads, tutorials and interviews.
An HDR LoRA fine-tune for Lightricks' LTX-2.3 (22B) that enables image‑conditioned any‑to‑any image-to-video and text-to-video generation. Designed for HDR-aware synthesis workflows; requires the LTX-2.3 base model and a LoRA-capable runtime.
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.
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.
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.