activity
20222025
most citedFew-shot Image Generation with Diffusion Models

14 citations · 45 across the 10 of their papers we have counts for

collaborators

13 papers

cs.CV2025

InstDrive: Instance-Aware 3D Gaussian Splatting for Driving Scenes

Hongyuan Liu, Haochen Yu, Bochao Zou +4

Reconstructing dynamic driving scenes from dashcam videos has attracted increasing attention due to its significance in autonomous driving and scene understanding. While recent adv…

cs.CV2025

MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network

Jianfei Jiang, Qiankun Liu, Haochen Yu +4

Learning-based Multi-View Stereo (MVS) methods aim to predict depth maps for a sequence of calibrated images to recover dense point clouds. However, existing MVS methods often stru…

cs.CV2025

Kaleidoscopic Background Attack: Disrupting Pose Estimation with Multi-Fold Radial Symmetry Textures

Xinlong Ding, Hongwei Yu, Jiawei Li +5

Camera pose estimation is a fundamental computer vision task that is essential for applications like visual localization and multi-view stereo reconstruction. In the object-centric…

cs.CV2024

TopV-Nav: Unlocking the Top-View Spatial Reasoning Potential of MLLM for Zero-shot Object Navigation

Linqing Zhong, Chen Gao, Zihan Ding +5

The Zero-Shot Object Navigation (ZSON) task requires embodied agents to find a previously unseen object by navigating in unfamiliar environments. Such a goal-oriented exploration h…

cs.CV2024★ 5 cited

ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models

Jingyuan Zhu, Shiyu Li, Yuxuan Liu +4

Modern diffusion-based image generative models have made significant progress and become promising to enrich training data for the object detection task. However, the generation qu…

cs.CV2024★ 1 cited

Isolated Diffusion: Optimizing Multi-Concept Text-to-Image Generation Training-Freely with Isolated Diffusion Guidance

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Large-scale text-to-image diffusion models have achieved great success in synthesizing high-quality and diverse images given target text prompts. Despite the revolutionary image ge…

cs.CV2023★ 1 cited

Learning a Graph Neural Network with Cross Modality Interaction for Image Fusion

Jiawei Li, Jiansheng Chen, Jinyuan Liu +1

Infrared and visible image fusion has gradually proved to be a vital fork in the field of multi-modality imaging technologies. In recent developments, researchers not only focus on…

cs.CV2023★ 2 cited

DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Typic…

cs.CV2023

Few-shot 3D Shape Generation

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Realistic and diverse 3D shape generation is helpful for a wide variety of applications such as virtual reality, gaming, and animation. Modern generative models, such as GANs and d…

cs.CV2023★ 10 cited

MotionVideoGAN: A Novel Video Generator Based on the Motion Space Learned from Image Pairs

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Video generation has achieved rapid progress benefiting from high-quality renderings provided by powerful image generators. We regard the video synthesis task as generating a seque…

cs.CV2023★ 1 cited

Distribution Aligned Feature Clustering for Zero-Shot Sketch-Based Image Retrieval

Yuchen Wu, Kun Song, Fangzheng Zhao +2

Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is a challenging cross-modal retrieval task. In prior arts, the retrieval is conducted by sorting the distance between the query sk…

cs.CV2022★ 14 cited

Few-shot Image Generation with Diffusion Models

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Howev…

cs.CV2022★ 11 cited

Few-shot Image Generation via Masked Discrimination

Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1

Few-shot image generation aims to generate images of high quality and great diversity with limited data. However, it is difficult for modern GANs to avoid overfitting when trained…