LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation,
  Generation and Editing
LLaVA-Interactive is a research prototype for multimodal human-AI
interaction. The system can have multi-turn dialogues with human users by
taking multimodal user inputs and generating multimodal responses. Importantly,
LLaVA-Interactive goes beyond language prompt, where visual prompt is enabled
to align human intents in the interaction. The development of LLaVA-Interactive
is extremely cost-efficient as the system combines three multimodal skills of
pre-built AI models without additional model training: visual chat of LLaVA,
image segmentation from SEEM, as well as image generation and editing from
GLIGEN. A diverse set of application scenarios is presented to demonstrate the
promises of LLaVA-Interactive and to inspire future research in multimodal
interactive systems.
65430d5fd292675f292f615d
Wei-Ge Chen
65430d5fd292675f292f615e
Irina Spiridonova
admin_assigned
2023-11-02T11:36:59.850Z
64dc0405ff83b3386a56677f
/avatars/6acccc389f1b0c8956d601ccaaf4503d.svg
Irina Spiridonova
user
Irinasp
65430d5fd292675f292f615f
Jianwei Yang
admin_assigned
2023-11-02T11:37:30.601Z
6125df7f25027fb1ea9c7a41
https://cdn-avatars.huggingface.co/v1/production/uploads/1629871954341-noauth.jpeg
Jianwei Yang
user
jw2yang
65430d5fd292675f292f6160
Jianfeng Gao
admin_assigned
2023-11-02T11:37:37.725Z
641904caf9d6f1d772ec7af7
/avatars/4a63eac71eb30f70b1a0e9d4708f26c1.svg
Jianfeng Gao
user
wyngjf
65430d5fd292675f292f6161
Chunyuan Li
admin_assigned
2023-11-02T11:37:45.100Z
62aba526cae4462c0c6caa0f
/avatars/430560ec2c2547f819225769ab432f30.svg
Chunyuan Li
user
Chunyuan24
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation,
  Generation and Editing
LLaVA-Interactive is a research prototype for multimodal human-AI
interaction. The system can have multi-turn dialogues with human users by
taking multimodal user inputs and generating multimodal responses. Importantly,
LLaVA-Interactive goes beyond language prompt, where visual prompt is enabled
to align human intents in the interaction. The development of LLaVA-Interactive
is extremely cost-efficient as the system combines three multimodal skills of
pre-built AI models without additional model training: visual chat of LLaVA,
image segmentation from SEEM, as well as image generation and editing from
GLIGEN. A diverse set of application scenarios is presented to demonstrate the
promises of LLaVA-Interactive and to inspire future research in multimodal
interactive systems.
LLaVA-Interactive is a cost-efficient multimodal dialogue system that integrates visual chat, image segmentation, and generation capabilities to enhance human-AI interaction.
multimodal human-AI interaction dialogues multimodal inputs visual prompt pre-built AI models visual chat image segmentation image generation image editing multimodal skills