OmniCompass: A Holistic Benchmark for Omni-Modal Video Grounding and Understanding
SALMONN family: A suite of advanced multi-modal LLMs
Give AI agents eyes, ears, and verifiable results. Watch Skill turns video, audio and screen activity into searchable, timestamped evidence and proves work with deterministic contracts, not model opinion. DeepWatch is the agent workspace built on DeepSeek Harness. Python + npm, MCP, CLI, REST, Web.
Code as World: Agentic Discovery of Executable World Representations for Physical Reasoning
One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks
GLM-4.6V/4.5V/4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.
awesome grounding: A curated list of research papers in visual grounding
An open-weight 11B model series for long-form and real-time video understanding
TLive-Omni: An Omni-Modal Understanding Model for E-Commerce Live Streaming
Self-hosted AI video analysis: summaries, chapters, keyframes, transcripts and SRT / JSON export. AI 视频总结、字幕提取与结构化分析。
CDAF (Cached Descriptive Asset Files) - open sidecar format for video so AI agents stop re-analyzing the same footage. Spec, CLI, agent skill, reproducible benchmark.
🚀🚀 A multimodal System One decision model that gives calibrated answers to typed questions about screens, photos, video and text in one forward pass.
🎬 OraRL — Annotations as Rollouts for efficient, scalable reinforcement learning of unified video MLLMs.
Native-video memory for vision-language-action models, using timestamped visual history and exact streaming inference for long-horizon robot manipulation.
Learning Spatial Reasoning through Interaction with the Observable Physical World
Official implementation of "Beyond the Timeline: Augmenting Long-Video Memory with Grounded Entity Biographies"
让任何 AI 真正"看"视频:纯本地的视频阅读 skill——faster-whisper GPU 转写 + ffmpeg 场景感知抽帧,双通道带时间戳(t=MM:SS),数据不出机。1 小时视频 3~5 分钟读完。Give any AI agent eyes for video: 100% local video-reading skill — faster-whisper GPU transcription + scene-aware ffmpeg frame extraction, dual-channel with t=MM:SS citations. Nothing leaves your machine.
Give your agent eyes: any video link in, one typed JSON out. A Claude skill + API.
🔥🔥🔥 [IEEE TCSVT] Latest Papers, Codes and Datasets on Vid-LLMs.
[Preprint 2026] StreamOPD: A Post-Training Recipe with Spatio-Temporal Cue Gating for Streaming Video Understanding