120 citations · 306 across the 22 of their papers we have counts for
13 papers · 2 filters
RTMW: Real-Time Multi-Person 2D and 3D Whole-body Pose Estimation
Tao Jiang, Xinchen Xie, Yining Li
Whole-body pose estimation is a challenging task that requires simultaneous prediction of keypoints for the body, hands, face, and feet. Whole-body pose estimation aims to predict…
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
Pan Zhang, Xiaoyi Dong, Yuhang Zang +24
We present InternLM-XComposer-2.5 (IXC-2.5), a versatile large-vision language model that supports long-contextual input and output. IXC-2.5 excels in various text-image comprehens…
MG-LLaVA: Towards Multi-Granularity Visual Instruction Tuning
Xiangyu Zhao, Xiangtai Li, Haodong Duan +4
Multi-modal large language models (MLLMs) have made significant strides in various visual understanding tasks. However, the majority of these models are constrained to process low-…
Auto Cherry-Picker: Learning from High-quality Generative Data Driven by Language
Yicheng Chen, Xiangtai Li, Yining Li +4
Diffusion models can generate realistic and diverse images, potentially facilitating data availability for data-intensive perception tasks. However, leveraging these models to boos…
MotionBooth: Motion-Aware Customized Text-to-Video Generation
Jianzong Wu, Xiangtai Li, Yanhong Zeng +5
In this work, we present MotionBooth, an innovative framework designed for animating customized subjects with precise control over both object and camera movements. By leveraging a…
MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding
Xinyu Fang, Kangrui Mao, Haodong Duan +4
The advent of large vision-language models (LVLMs) has spurred research into their applications in multi-modal contexts, particularly in video understanding. Traditional VideoQA be…
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Xiaoyi Dong, Pan Zhang, Yuhang Zang +21
The Large Vision-Language Model (LVLM) field has seen significant advancements, yet its progression has been hindered by challenges in comprehending fine-grained visual content due…
InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model
Xiaoyi Dong, Pan Zhang, Yuhang Zang +20
We introduce InternLM-XComposer2, a cutting-edge vision-language model excelling in free-form text-image composition and comprehension. This model goes beyond conventional vision-l…
An Open and Comprehensive Pipeline for Unified Object Grounding and Detection
Xiangyu Zhao, Yicheng Chen, Shilin Xu +4
Grounding-DINO is a state-of-the-art open-set detection model that tackles multiple vision tasks including Open-Vocabulary Detection (OVD), Phrase Grounding (PG), and Referring Exp…
OMG-Seg: Is One Model Good Enough For All Segmentation?
Xiangtai Li, Haobo Yuan, Wei Li +6
In this work, we address various segmentation tasks, each traditionally tackled by distinct or partially unified models. We propose OMG-Seg, One Model that is Good enough to effici…
RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything
Shilin Xu, Haobo Yuan, Qingyu Shi +9
Recent segmentation methods, which adopt large-scale data training and transformer architecture, aim to create one foundation model that can perform multiple tasks. However, most o…
Towards Language-Driven Video Inpainting via Multimodal Large Language Models
Jianzong Wu, Xiangtai Li, Chenyang Si +8
We introduce a new task -- language-driven video inpainting, which uses natural language instructions to guide the inpainting process. This approach overcomes the limitations of tr…
Open-Vocabulary SAM: Segment and Recognize Twenty-thousand Classes Interactively
Haobo Yuan, Xiangtai Li, Chong Zhou +3
The CLIP and Segment Anything Model (SAM) are remarkable vision foundation models (VFMs). SAM excels in segmentation tasks across diverse domains, whereas CLIP is renowned for its…