62 citations · 173 across the 23 of their papers we have counts for
23 papers
Aligned Stable Inpainting: Mitigating Unwanted Object Insertion and Preserving Color Consistency
Yikai Wang, Junqiu Yu, Chenjie Cao +2
Generative image inpainting can produce realistic results even with large, irregular masks, but existing methods still suffer from two common problems: (1) Unwanted object insertio…
AnyRefill: A Unified, Data-Efficient Framework for Left-Prompt-Guided Vision Tasks
Ming Xie, Chenjie Cao, Yunuo Cai +3
In this paper, we present a novel Left-Prompt-Guided (LPG) paradigm to address a diverse range of reference-based vision tasks. Inspired by the human creative process, we reformula…
Improving Neural Surface Reconstruction with Feature Priors from Multi-View Image
Xinlin Ren, Chenjie Cao, Yanwei Fu +1
Recent advancements in Neural Surface Reconstruction (NSR) have significantly improved multi-view reconstruction when coupled with volume rendering. However, relying solely on phot…
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo
Chenjie Cao, Xinlin Ren, Yanwei Fu
Recent advancements in learning-based Multi-View Stereo (MVS) methods have prominently featured transformer-based models with attention mechanisms. However, existing approaches hav…
Repositioning the Subject within Image
Yikai Wang, Chenjie Cao, Ke Fan +4
Current image manipulation primarily centers on static manipulation, such as replacing specific regions within an image or altering its overall style. In this paper, we introduce a…
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…
ZITS++: Image Inpainting by Improving the Incremental Transformer on Structural Priors
Chenjie Cao, Qiaole Dong, Yanwei Fu
Image inpainting involves filling missing areas of a corrupted image. Despite impressive results have been achieved recently, restoring images with both vivid textures and reasonab…
MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth
Chenjie Cao, Xinlin Ren, Yanwei Fu
Feature representation learning is the key recipe for learning-based Multi-View Stereo (MVS). As the common feature extractor of learning-based MVS, vanilla Feature Pyramid Network…
Learning Prior Feature and Attention Enhanced Image Inpainting
Chenjie Cao, Qiaole Dong, Yanwei Fu
Many recent inpainting works have achieved impressive results by leveraging Deep Neural Networks (DNNs) to model various prior information for image restoration. Unfortunately, the…
Wavelet Prior Attention Learning in Axial Inpainting Network
Chenjie Cao, Chengrong Wang, Yuntao Zhang +1
Image inpainting is the task of filling masked or unknown regions of an image with visually realistic contents, which has been remarkably improved by Deep Neural Networks (DNNs) re…
Pixel2Mesh++: 3D Mesh Generation and Refinement from Multi-View Images
Chao Wen, Yinda Zhang, Chenjie Cao +3
We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate…
Incremental Transformer Structure Enhanced Image Inpainting with Masking Positional Encoding
Qiaole Dong, Chenjie Cao, Yanwei Fu
Image inpainting has made significant advances in recent years. However, it is still challenging to recover corrupted images with both vivid textures and reasonable structures. Som…
The Image Local Autoregressive Transformer
Chenjie Cao, Yuxin Hong, Xiang Li +4
Recently, AutoRegressive (AR) models for the whole image generation empowered by transformers have achieved comparable or even better performance to Generative Adversarial Networks…
Learning a Sketch Tensor Space for Image Inpainting of Man-made Scenes
Chenjie Cao, Yanwei Fu
This paper studies the task of inpainting man-made scenes. It is very challenging due to the difficulty in preserving the visual patterns of images, such as edges, lines, and junct…
CLUE: A Chinese Language Understanding Evaluation Benchmark
Liang Xu, Hai Hu, Xuanwei Zhang +29
The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks. These com…
Learning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition
Wenxuan Wang, Yanwei Fu, Qiang Sun +7
Affective computing and cognitive theory are widely used in modern human-computer interaction scenarios. Human faces, as the most prominent and easily accessible features, have att…
A Fine-Grained Facial Expression Database for End-to-End Multi-Pose Facial Expression Recognition
Wenxuan Wang, Qiang Sun, Tao Chen +5
The recent research of facial expression recognition has made a lot of progress due to the development of deep learning technologies, but some typical challenging problems such as…
Multimodal Emotion Recognition for One-Minute-Gradual Emotion Challenge
Ziqi Zheng, Chenjie Cao, Xingwei Chen +1
The continuous dimensional emotion modelled by arousal and valence can depict complex changes of emotions. In this paper, we present our works on arousal and valence predictions fo…