32 citations · 44 across the 22 of their papers we have counts for
10 papers · 2 filters
REO-VLM: Transforming VLM to Meet Regression Challenges in Earth Observation
Xizhe Xue, Guoting Wei, Hao Chen +4
The rapid evolution of Vision Language Models (VLMs) has catalyzed significant advancements in artificial intelligence, expanding research across various disciplines, including Ear…
Framer: Interactive Frame Interpolation
Wen Wang, Qiuyu Wang, Kecheng Zheng +6
We propose Framer for interactive frame interpolation, which targets producing smoothly transitioning frames between two images as per user creativity. Concretely, besides taking t…
TG-LLaVA: Text Guided LLaVA via Learnable Latent Embeddings
Dawei Yan, Pengcheng Li, Yang Li +7
Currently, inspired by the success of vision-language models (VLMs), an increasing number of researchers are focusing on improving VLMs and have achieved promising results. However…
FreeCompose: Generic Zero-Shot Image Composition with Diffusion Prior
Zhekai Chen, Wen Wang, Zhen Yang +3
We offer a novel approach to image composition, which integrates multiple input images into a single, coherent image. Rather than concentrating on specific use cases such as appear…
MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequence
Canyu Zhao, Mingyu Liu, Wen Wang +5
Recent advancements in video generation have primarily leveraged diffusion models for short-duration content. However, these approaches often fall short in modeling complex narrati…
Generative Active Learning for Long-tailed Instance Segmentation
Muzhi Zhu, Chengxiang Fan, Hao Chen +4
Recently, large-scale language-image generative models have gained widespread attention and many works have utilized generated data from these models to further enhance the perform…
FreeCustom: Tuning-Free Customized Image Generation for Multi-Concept Composition
Ganggui Ding, Canyu Zhao, Wen Wang +4
Benefiting from large-scale pre-trained text-to-image (T2I) generative models, impressive progress has been achieved in customized image generation, which aims to generate user-spe…
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data
Chengxiang Fan, Muzhi Zhu, Hao Chen +4
Instance segmentation is data-hungry, and as model capacity increases, data scale becomes crucial for improving the accuracy. Most instance segmentation datasets today require cost…
Zippo: Zipping Color and Transparency Distributions into a Single Diffusion Model
Kangyang Xie, Binbin Yang, Hao Chen +5
Beyond the superiority of the text-to-image diffusion model in generating high-quality images, recent studies have attempted to uncover its potential for adapting the learned seman…
Diffusion Models are Efficient Data Generators for Human Mesh Recovery
Yongtao Ge, Wenjia Wang, Yongfan Chen +4
Despite remarkable progress having been made on the problem of 3D human pose and shape estimation (HPS), current state-of-the-art methods rely heavily on either confined indoor moc…