54 citations · 227 across the 28 of their papers we have counts for
17 papers · 1 filter
BEVHeight++: Toward Robust Visual Centric 3D Object Detection
Lei Yang, Tao Tang, Jun Li +6
While most recent autonomous driving system focuses on developing perception methods on ego-vehicle sensors, people tend to overlook an alternative approach to leverage intelligent…
Unified Pre-training with Pseudo Texts for Text-To-Image Person Re-identification
Zhiyin Shao, Xinyu Zhang, Changxing Ding +2
The pre-training task is indispensable for the text-to-image person re-identification (T2I-ReID) task. However, there are two underlying inconsistencies between these two tasks tha…
InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition
Pan Zhang, Xiaoyi Dong, Bin Wang +18
We propose InternLM-XComposer, a vision-language large model that enables advanced image-text comprehension and composition. The innovative nature of our model is highlighted by th…
DEFormer: DCT-driven Enhancement Transformer for Low-light Image and Dark Vision
Xiangchen Yin, Zhenda Yu, Xin Gao +1
Low-light image enhancement restores the colors and details of a single image and improves high-level visual tasks. However, restoring the lost details in the dark area is still a…
SkipcrossNets: Adaptive Skip-cross Fusion for Road Detection
Yan Gong, Xinyu Zhang, Hao Liu +7
Multi-modal fusion is increasingly being used for autonomous driving tasks, as different modalities provide unique information for feature extraction. However, the existing two-str…
Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification
Pei Liu, Luping Ji, Xinyu Zhang +1
Given the special situation of modeling gigapixel images, multiple instance learning (MIL) has become one of the most important frameworks for Whole Slide Image (WSI) classificatio…
BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection
Lei Yang, Kaicheng Yu, Tao Tang +5
While most recent autonomous driving system focuses on developing perception methods on ego-vehicle sensors, people tend to overlook an alternative approach to leverage intelligent…
FastPillars: A Deployment-friendly Pillar-based 3D Detector
Sifan Zhou, Zhi Tian, Xiangxiang Chu +7
The deployment of 3D detectors strikes one of the major challenges in real-world self-driving scenarios. Existing BEV-based (i.e., Bird Eye View) detectors favor sparse convolution…
CAE v2: Context Autoencoder with CLIP Target
Xinyu Zhang, Jiahui Chen, Junkun Yuan +10
Masked image modeling (MIM) learns visual representation by masking and reconstructing image patches. Applying the reconstruction supervision on the CLIP representation has been pr…
MTCSNN: Multi-task Clinical Siamese Neural Network for Diabetic Retinopathy Severity Prediction
Chao Feng, Jui Po Hung, Aishan Li +2
Diabetic Retinopathy (DR) has become one of the leading causes of vision impairment in working-aged people and is a severe problem worldwide. However, most of the works ignored the…
UFO: Unified Feature Optimization
Teng Xi, Yifan Sun, Deli Yu +13
This paper proposes a novel Unified Feature Optimization (UFO) paradigm for training and deploying deep models under real-world and large-scale scenarios, which requires a collecti…
Learning Granularity-Unified Representations for Text-to-Image Person Re-identification
Zhiyin Shao, Xinyu Zhang, Meng Fang +3
Text-to-image person re-identification (ReID) aims to search for pedestrian images of an interested identity via textual descriptions. It is challenging due to both rich intra-moda…
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object Detection
Lei Yang, Xinyu Zhang, Li Wang +3
Monocular 3D object detection is an essential perception task for autonomous driving. However, the high reliance on large-scale labeled data make it costly and time-consuming durin…
Implicit Sample Extension for Unsupervised Person Re-Identification
Xinyu Zhang, Dongdong Li, Zhigang Wang +5
Most existing unsupervised person re-identification (Re-ID) methods use clustering to generate pseudo labels for model training. Unfortunately, clustering sometimes mixes different…
Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory
Xinyu Zhang, Dong Gong, Jiewei Cao +1
Unsupervised cross-domain person re-identification (Re-ID) aims to adapt the information from the labelled source domain to an unlabelled target domain. Due to the lack of supervis…
Part-Guided Attention Learning for Vehicle Instance Retrieval
Xinyu Zhang, Rufeng Zhang, Jiewei Cao +3
Vehicle instance retrieval often requires one to recognize the fine-grained visual differences between vehicles. Besides the holistic appearance of vehicles which is easily affecte…
Self-training with progressive augmentation for unsupervised cross-domain person re-identification
Xinyu Zhang, Jiewei Cao, Chunhua Shen +1
Person re-identification (Re-ID) has achieved great improvement with deep learning and a large amount of labelled training data. However, it remains a challenging task for adapting…