2 citations · 7 across the 23 of their papers we have counts for
12 papers · 1 filter
Kestrel: Grounding Self-Refinement for LVLM Hallucination Mitigation
Jiawei Mao, Hardy Chen, Haoqin Tu +7
Large vision-language models (LVLMs) have become increasingly strong but remain prone to hallucinations in multimodal tasks, which significantly narrows their deployment. As traini…
A Unified and Controllable Framework for Layered Image Generation with Visual Effects
Jinrui Yang, Qing Liu, Yijun Li +5
Recent image generation models produce impressive composites, but often fail to preserve the identity of user-provided content when editing specific elements: the surrounding scene…
OpenVision 2: A Family of Generative Pretrained Visual Encoders for Multimodal Learning
Yanqing Liu, Xianhang Li, Letian Zhang +4
This paper provides a simplification on OpenVision's architecture and loss design for enhancing its training efficiency. Following the prior vision-language pretraining works CapPa…
GPT-IMAGE-EDIT-1.5M: A Million-Scale, GPT-Generated Image Dataset
Yuhan Wang, Siwei Yang, Bingchen Zhao +4
Recent advancements in large multimodal models like GPT-4o have set a new standard for high-fidelity, instruction-guided image editing. However, the proprietary nature of these mod…
EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models
GuangHao Meng, Sunan He, Jinpeng Wang +7
Vision-language retrieval (VLR) has attracted significant attention in both academia and industry, which involves using text (or images) as queries to retrieve corresponding images…
Oasis: One Image is All You Need for Multimodal Instruction Data Synthesis
Letian Zhang, Quan Cui, Bingchen Zhao +1
The success of multi-modal large language models (MLLMs) has been largely attributed to the large-scale training data. However, the training data of many MLLMs is unavailable due t…
Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning
Bingchen Zhao, Yongshuo Zong, Letian Zhang +1
The advancement of large language models (LLMs) has significantly broadened the scope of applications in natural language processing, with multi-modal LLMs extending these capabili…
ImageNet3D: Towards General-Purpose Object-Level 3D Understanding
Wufei Ma, Guanning Zeng, Guofeng Zhang +5
A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D (e.g., class name and bounding box) and 3D information (e.g., 3D location a…
Pre-Trained Vision-Language Models as Partial Annotators
Qian-Wei Wang, Yuqiu Xie, Letian Zhang +2
Pre-trained vision-language models learn massive data to model unified representations of images and natural languages, which can be widely applied to downstream machine learning t…
IL-NeRF: Incremental Learning for Neural Radiance Fields with Camera Pose Alignment
Letian Zhang, Ming Li, Chen Chen +1
Neural radiance fields (NeRF) is a promising approach for generating photorealistic images and representing complex scenes. However, when processing data sequentially, it can suffe…
Envisioning a Next Generation Extended Reality Conferencing System with Efficient Photorealistic Human Rendering
Chuanyue Shen, Letian Zhang, Zhangsihao Yang +4
Meeting online is becoming the new normal. Creating an immersive experience for online meetings is a necessity towards more diverse and seamless environments. Efficient photorealis…
EPose: Energy-Efficient Edge-assisted Multi-camera System for Multi-human 3D Pose Estimation
Letian Zhang, Jie Xu
Multi-human 3D pose estimation plays a key role in establishing a seamless connection between the real world and the virtual world. Recent efforts adopted a two-stage framework tha…