5 citations · 12 across the 6 of their papers we have counts for
6 papers · 1 filter
Learning to Adapt Category Consistent Meta-Feature of CLIP for Few-Shot Classification
Jiaying Shi, Xuetong Xue, Shenghui Xu
The recent CLIP-based methods have shown promising zero-shot and few-shot performance on image classification tasks. Existing approaches such as CoOp and Tip-Adapter only focus on…
MindSemantix: Deciphering Brain Visual Experiences with a Brain-Language Model
Ziqi Ren, Jie Li, Xuetong Xue +4
Deciphering the human visual experience through brain activities captured by fMRI represents a compelling and cutting-edge challenge in the field of neuroscience research. Compared…
Cross-Scale Context Extracted Hashing for Fine-Grained Image Binary Encoding
Xuetong Xue, Jiaying Shi, Xinxue He +2
Deep hashing has been widely applied to large-scale image retrieval tasks owing to efficient computation and low storage cost by encoding high-dimensional image data into binary co…
2nd Place Solution to Google Landmark Retrieval 2020
Min Yang, Cheng Cui, Xuetong Xue +2
This paper presents the 2nd place solution to the Google Landmark Retrieval Competition 2020. We propose a training method of global feature model for landmark retrieval without po…
DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features
Min Yang, Dongliang He, Miao Fan +5
Image Retrieval is a fundamental task of obtaining images similar to the query one from a database. A common image retrieval practice is to firstly retrieve candidate images via si…
Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning
Ziqi Ren, Jie Li, Xuetong Xue +4
Reconstructing visual stimulus (image) only from human brain activity measured with functional Magnetic Resonance Imaging (fMRI) is a significant and meaningful task in Human-AI co…