bytedance / video-SALMONN-2Links
video-SALMONN 2 is a powerful audio-visual large language model (LLM) that generates high-quality audio-visual video captions, which is developed by the Department of Electronic Engineering at Tsinghua University and ByteDance.
☆94Updated this week
Alternatives and similar repositories for video-SALMONN-2
Users that are interested in video-SALMONN-2 are comparing it to the libraries listed below
Sorting:
- ☆78Updated 7 months ago
- ☆78Updated 5 months ago
- Video dataset dedicated to portrait-mode video recognition.☆52Updated last week
- Official PyTorch implementation of EMOVA in CVPR 2025 (https://arxiv.org/abs/2409.18042)☆73Updated 7 months ago
- Official implementation of paper AdaReTaKe: Adaptive Redundancy Reduction to Perceive Longer for Video-language Understanding☆85Updated 6 months ago
- ☆176Updated 8 months ago
- Ming - facilitating advanced multimodal understanding and generation capabilities built upon the Ling LLM.☆481Updated last month
- A new multi-shot video understanding benchmark Shot2Story with comprehensive video summaries and detailed shot-level captions.☆157Updated 8 months ago
- The official repo for "Vidi: Large Multimodal Models for Video Understanding and Editing"☆141Updated last month
- [CVPR 2025]Dispider: Enabling Video LLMs with Active Real-Time Interaction via Disentangled Perception, Decision, and Reaction☆139Updated 7 months ago
- ☆130Updated 2 months ago
- ☆35Updated 2 months ago
- (ICCV2025) Official repository of paper "ViSpeak: Visual Instruction Feedback in Streaming Videos"☆40Updated 3 months ago
- Kling-Foley: Multimodal Diffusion Transformer for High-Quality Video-to-Audio Generation☆59Updated 4 months ago
- This is the official implementation of ICCV 2025 "Flash-VStream: Efficient Real-Time Understanding for Long Video Streams"☆238Updated last week
- ☆34Updated 4 months ago
- LMM solved catastrophic forgetting, AAAI2025☆44Updated 6 months ago
- LLaVA combines with Magvit Image tokenizer, training MLLM without an Vision Encoder. Unifying image understanding and generation.☆37Updated last year
- [ICCV 2025] Explore the Limits of Omni-modal Pretraining at Scale☆118Updated last year
- [ICLR 2025] AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark☆129Updated 4 months ago
- A Simple Framework of Small-scale LMMs for Video Understanding☆94Updated 4 months ago
- ☆130Updated last week
- [CVPR 2024] Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners☆150Updated last year
- [NIPS2025] VideoChat-R1 & R1.5: Enhancing Spatio-Temporal Perception and Reasoning via Reinforcement Fine-Tuning☆215Updated last week
- Structured Video Comprehension of Real-World Shorts☆208Updated last month
- ☆58Updated 3 months ago
- [Arxiv 2024] Official code for MMTrail: A Multimodal Trailer Video Dataset with Language and Music Descriptions☆33Updated 8 months ago
- ☆194Updated last year
- [NeurIPS 2025] HermesFlow: Seamlessly Closing the Gap in Multimodal Understanding and Generation☆71Updated last month
- [ICCV 2025] Official Repository of VideoLLaMB: Long Video Understanding with Recurrent Memory Bridges☆77Updated 7 months ago