most citedOne Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos

4 citations · 6 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Factorized Visual Tokenization and Generation

Zechen Bai, Jianxiong Gao, Ziteng Gao +4

Visual tokenizers are fundamental to image generation. They convert visual data into discrete tokens, enabling transformer-based models to excel at image generation. Despite their…

cs.CV2024

VideoSAM: Open-World Video Segmentation

Pinxue Guo, Zixu Zhao, Jianxiong Gao +5

Video segmentation is essential for advancing robotics and autonomous driving, particularly in open-world settings where continuous perception and object association across video f…

cs.CV20244 cited

One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos

Zechen Bai, Tong He, Haiyang Mei +6

We introduce VideoLISA, a video-based multimodal large language model designed to tackle the problem of language-instructed reasoning segmentation in videos. Leveraging the reasoni…

cs.CV2024

Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation

Jiaxin Cheng, Zixu Zhao, Tong He +3

Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion an…

cs.CV2024

Bridging Information Asymmetry in Text-video Retrieval: A Data-centric Approach

Zechen Bai, Tianjun Xiao, Tong He +4

As online video content rapidly grows, the task of text-video retrieval (TVR) becomes increasingly important. A key challenge in TVR is the information asymmetry between video and…

cs.CV2024

Hallucination of Multimodal Large Language Models: A Survey

Zechen Bai, Pichao Wang, Tianjun Xiao +4

This survey presents a comprehensive analysis of the phenomenon of hallucination in multimodal large language models (MLLMs), also known as Large Vision-Language Models (LVLMs), wh…