62 citations · 173 across the 23 of their papers we have counts for
6 papers · 1 filter
Towards Enhanced Image Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency
Yikai Wang, Chenjie Cao, Junqiu Yu +3
Recent advances in image inpainting increasingly use generative models to handle large irregular masks. However, these models can create unrealistic inpainted images due to two mai…
Local Consensus Enhanced Siamese Network with Reciprocal Loss for Two-view Correspondence Learning
Linbo Wang, Jing Wu, Xianyong Fang +3
Recent studies of two-view correspondence learning usually establish an end-to-end network to jointly predict correspondence reliability and relative pose. We improve such a framew…
LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion Model
Chenjie Cao, Yunuo Cai, Qiaole Dong +2
This paper introduces LeftRefill, an innovative approach to efficiently harness large Text-to-Image (T2I) diffusion models for reference-guided image synthesis. As the name implies…
Rethinking Optical Flow from Geometric Matching Consistent Perspective
Qiaole Dong, Chenjie Cao, Yanwei Fu
Optical flow estimation is a challenging problem remaining unsolved. Recent deep learning based optical flow models have achieved considerable success. However, these models often…
Rethinking the Multi-view Stereo from the Perspective of Rendering-based Augmentation
Chenjie Cao, Xinlin Ren, Xiangyang Xue +1
GigaMVS presents several challenges to existing Multi-View Stereo (MVS) algorithms for its large scale, complex occlusions, and gigapixel images. To address these problems, we firs…
Improving Transformer-based Image Matching by Cascaded Capturing Spatially Informative Keypoints
Chenjie Cao, Yanwei Fu
Learning robust local image feature matching is a fundamental low-level vision task, which has been widely explored in the past few years. Recently, detector-free local feature mat…