61 citations · 93 across the 8 of their papers we have counts for
9 papers
DIGS: Distribution-Informed Gaussian Splatting for Training-Free Open-Vocabulary 3D Segmentation
Zhifan Zeng, Wenbo Xiao, Arcot Sowmya +1
Open-vocabulary 3D Gaussian segmentation typically binds semantic features to the per-Gaussian state via per-scene gradient training (1-4 h) or the more recent closed-form distilla…
Second-order Anisotropic Gaussian Directional Derivative Filters for Blob Detection
Jie Ren, Wenya Yu, Jiapan Guo +2
Interest point detection methods have received increasing attention and are widely used in computer vision tasks such as image retrieval and 3D reconstruction. In this work, second…
Learning Partial Correlation based Deep Visual Representation for Image Classification
Saimunur Rahman, Piotr Koniusz, Lei Wang +3
Visual representation based on covariance matrix has demonstrates its efficacy for image classification by characterising the pairwise correlation of different channels in convolut…
Calibrating a Deep Neural Network with Its Predecessors
Linwei Tao, Minjing Dong, Daochang Liu +2
Confidence calibration - the process to calibrate the output probability distribution of neural networks - is essential for safety-critical applications of such networks. Recent wo…
EOCSA: Predicting Prognosis of Epithelial Ovarian Cancer with Whole Slide Histopathological Images
Tianling Liu, Ran Su, Changming Sun +2
Ovarian cancer is one of the most serious cancers that threaten women around the world. Epithelial ovarian cancer (EOC), as the most commonly seen subtype of ovarian cancer, has ra…
Improving Monocular Visual Odometry Using Learned Depth
Libo Sun, Wei Yin, Enze Xie +3
Monocular visual odometry (VO) is an important task in robotics and computer vision. Thus far, how to build accurate and robust monocular VO systems that can work well in diverse s…
NDPNet: A novel non-linear data projection network for few-shot fine-grained image classification
Weichuan Zhang, Xuefang Liu, Zhe Xue +2
Metric-based few-shot fine-grained image classification (FSFGIC) aims to learn a transferable feature embedding network by estimating the similarities between query images and supp…
Image Feature Information Extraction for Interest Point Detection: A Review
Junfeng Jing, Tian Gao, Weichuan Zhang +2
Interest point detection is one of the most fundamental and critical problems in computer vision and image processing. In this paper, we carry out a comprehensive review on image f…
Free-form tumor synthesis in computed tomography images via richer generative adversarial network
Qiangguo Jin, Hui Cui, Changming Sun +2
The insufficiency of annotated medical imaging scans for cancer makes it challenging to train and validate data-hungry deep learning models in precision oncology. We propose a new…