16 citations · 28 across the 25 of their papers we have counts for
9 papers · 2 filters
InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language Models
Cong Wei, Yujie Zhong, Haoxian Tan +4
Boosted by Multi-modal Large Language Models (MLLMs), text-guided universal segmentation models for the image and video domains have made rapid progress recently. However, these me…
HyperSeg: Towards Universal Visual Segmentation with Large Language Model
Cong Wei, Yujie Zhong, Haoxian Tan +4
This paper aims to address universal segmentation for image and video perception with the strong reasoning ability empowered by Visual Large Language Models (VLLMs). Despite signif…
VISTA: Enhancing Long-Duration and High-Resolution Video Understanding by Video Spatiotemporal Augmentation
Weiming Ren, Huan Yang, Jie Min +2
Current large multimodal models (LMMs) face significant challenges in processing and comprehending long-duration or high-resolution videos, which is mainly due to the lack of high-…
OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision
Cong Wei, Zheyang Xiong, Weiming Ren +3
Instruction-guided image editing methods have demonstrated significant potential by training diffusion models on automatically synthesized or manually annotated image editing pairs…
MANTIS: Interleaved Multi-Image Instruction Tuning
Dongfu Jiang, Xuan He, Huaye Zeng +4
Large multimodal models (LMMs) have shown great results in single-image vision language tasks. However, their abilities to solve multi-image visual language tasks is yet to be impr…
LaSagnA: Language-based Segmentation Assistant for Complex Queries
Cong Wei, Haoxian Tan, Yujie Zhong +2
Recent advancements have empowered Large Language Models for Vision (vLLMs) to generate detailed perceptual outcomes, including bounding boxes and masks. Nonetheless, there are two…
AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Tasks
Max Ku, Cong Wei, Weiming Ren +2
In the dynamic field of digital content creation using generative models, state-of-the-art video editing models still do not offer the level of quality and control that users desir…
Towards Artwork Explanation in Large-scale Vision Language Models
Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2
Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…
ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation
Weiming Ren, Huan Yang, Ge Zhang +4
Image-to-video (I2V) generation aims to use the initial frame (alongside a text prompt) to create a video sequence. A grand challenge in I2V generation is to maintain visual consis…