127 citations · 168 across the 38 of their papers we have counts for
6 papers · 1 filter
GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning
Jiaxi Lv, Yi Huang, Mingfu Yan +6
Recent advances in text-to-video generation have harnessed the power of diffusion models to create visually compelling content conditioned on text prompts. However, they usually en…
ImageBind-LLM: Multi-modality Instruction Tuning
Jiaming Han, Renrui Zhang, Wenqi Shao +14
We present ImageBind-LLM, a multi-modality instruction tuning method of large language models (LLMs) via ImageBind. Existing works mainly focus on language and image instruction tu…
Baichuan 2: Open Large-scale Language Models
Aiyuan Yang, Bin Xiao, Bingning Wang +52
Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing…
DPL: Decoupled Prompt Learning for Vision-Language Models
Chen Xu, Yuhan Zhu, Guozhen Zhang +5
Prompt learning has emerged as an efficient and effective approach for transferring foundational Vision-Language Models (e.g., CLIP) to downstream tasks. However, current methods t…
Progressive Visual Prompt Learning with Contrastive Feature Re-formation
Chen Xu, Yuhan Zhu, Haocheng Shen +4
Prompt learning has been designed as an alternative to fine-tuning for adapting Vision-language (V-L) models to the downstream tasks. Previous works mainly focus on text prompt whi…
Real-Time Image Demoireing on Mobile Devices
Yuxin Zhang, Mingbao Lin, Xunchao Li +7
Moire patterns appear frequently when taking photos of digital screens, drastically degrading the image quality. Despite the advance of CNNs in image demoireing, existing networks…