research
∙
08/21/2023
Spatial Transform Decoupling for Oriented Object Detection
Vision Transformers (ViTs) have achieved remarkable success in computer ...
share
research
∙
07/19/2023
Generative Prompt Model for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) remains challenging when le...
research
∙
05/22/2023
Album Storytelling with Iterative Story-aware Captioning and Large Language Models
This work studies how to transform an album to vivid and coherent storie...
research
∙
02/28/2023
Generic-to-Specific Distillation of Masked Autoencoders
Large vision Transformers (ViTs) driven by self-supervised pre-training ...
research
∙
02/03/2023
Spectral Aware Softmax for Visible-Infrared Person Re-Identification
Visible-infrared person re-identification (VI-ReID) aims to match specif...
research
∙
01/29/2023
Unsupervised Domain Adaptation on Person Re-Identification via Dual-level Asymmetric Mutual Learning
Unsupervised domain adaptation person re-identification (Re-ID) aims to ...
research
∙
12/16/2022
DQnet: Cross-Model Detail Querying for Camouflaged Object Detection
Camouflaged objects are seamlessly blended in with their surroundings, w...
research
∙
12/15/2022
Proposal Distribution Calibration for Few-Shot Object Detection
Adapting object detectors learned with sufficient supervision to novel c...
research
∙
12/12/2022
Feature Calibration Network for Occluded Pedestrian Detection
Pedestrian detection in the wild remains a challenging problem especiall...
research
∙
12/12/2022
CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detection
Pedestrian detection in the wild remains a challenging problem especiall...
research
∙
11/23/2022
Integrally Pre-Trained Transformer Pyramid Networks
In this paper, we present an integral pre-training framework based on ma...
research
∙
11/02/2022
Beyond Instance Discrimination: Relation-aware Contrastive Self-supervised Learning
Contrastive self-supervised learning (CSL) based on instance discriminat...
research
∙
10/19/2022
A Unified View of Masked Image Modeling
Masked image modeling has demonstrated great potential to eliminate the ...
research
∙
10/17/2022
Multi-Agent Automated Machine Learning
In this paper, we propose multi-agent automated machine learning (MA2ML)...
research
∙
10/01/2022
Learnable Distribution Calibration for Few-Shot Class-Incremental Learning
Few-shot class-incremental learning (FSCIL) faces challenges of memorizi...
research
∙
08/12/2022
BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers
Masked image modeling (MIM) has demonstrated impressive results in self-...
research
∙
05/30/2022
HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling
Recently, masked image modeling (MIM) has offered a new methodology of s...
research
∙
05/19/2022
Integral Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection
Modern object detectors have taken the advantages of pre-trained vision ...
research
∙
04/17/2022
What Goes beyond Multi-modal Fusion in One-stage Referring Expression Comprehension: An Empirical Study
Most of the existing work in one-stage referring expression comprehensio...
research
∙
03/27/2022
Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers
The past year has witnessed a rapid development of masked image modeling...
research
∙
03/17/2022
Object Localization under Single Coarse Point Supervision
Point-based object localization (POL), which pursues high-performance ob...
research
∙
03/13/2022
Global2Local: A Joint-Hierarchical Attention for Video Captioning
Recently, automatic video captioning has attracted increasing attention,...
research
∙
01/26/2022
Mitigating the Mutual Error Amplification for Semi-Supervised Object Detection
Semi-supervised object detection (SSOD) has achieved substantial progres...
research
∙
12/31/2021
P2P-Loc: Point to Point Tiny Person Localization
Bounding-box annotation form has been the most frequently used method fo...
research
∙
12/05/2021
Exploring Complicated Search Spaces with Interleaving-Free Sampling
The existing neural architecture search algorithms are mostly working on...
research
∙
11/29/2021
Feature-Gate Coupling for Dynamic Network Pruning
Gating modules have been widely explored in dynamic network pruning to r...
research
∙
11/25/2021
Semantic-Aware Generation for Self-Supervised Visual Representation Learning
In this paper, we propose a self-supervised visual representation learni...
research
∙
10/06/2021
Long-tailed Distribution Adaptation
Recognizing images with long-tailed distributions remains a challenging ...
research
∙
09/17/2021
GraFormer: Graph Convolution Transformer for 3D Pose Estimation
Exploiting relations among 2D joints plays a crucial role yet remains se...
research
∙
09/12/2021
Prioritized Subnet Sampling for Resource-Adaptive Supernet Training
A resource-adaptive supernet adjusts its subnets for inference to fit th...
research
∙
07/23/2021
Adversarial Reinforced Instruction Attacker for Robust Vision-Language Navigation
Language instruction plays an essential role in the natural language gro...
research
∙
07/07/2021
Group Sampling for Unsupervised Person Re-identification
Unsupervised person re-identification (re-ID) remains a challenging task...
research
∙
06/20/2021
Cogradient Descent for Dependable Learning
Conventional gradient descent methods compute the gradients for multiple...
research
∙
06/01/2021
Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation
Encouraging progress in few-shot semantic segmentation has been made by ...
research
∙
05/24/2021
Towards Compact CNNs via Collaborative Compression
Channel pruning and tensor decomposition have received extensive attenti...
research
∙
05/09/2021
Conformer: Local Features Coupling Global Representations for Visual Recognition
Within Convolutional Neural Network (CNN), the convolution operations ar...
research
∙
04/06/2021
Multiple instance active learning for object detection
Despite the substantial progress of active learning for image recognitio...
research
∙
04/06/2021
Learnable Expansion-and-Compression Network for Few-shot Class-Incremental Learning
Few-shot class-incremental learning (FSCIL), which targets at continuous...
research
∙
03/27/2021
TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization
Weakly supervised object localization (WSOL) is a challenging problem wh...
research
∙
03/08/2021
Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection
Few-shot object detection has made substantial progressby representing n...
research
∙
01/20/2021
Non-Parametric Adaptive Network Pruning
Popular network pruning algorithms reduce redundant information by optim...
research
∙
11/19/2020
Towards Spatio-Temporal Video Scene Text Detection via Temporal Clustering
With only bounding-box annotations in the spatial domain, existing video...
research
∙
11/08/2020
Adaptive Linear Span Network for Object Skeleton Detection
Conventional networks for object skeleton detection are usually hand-cra...
research
∙
09/16/2020
The 1st Tiny Object Detection Challenge:Methods and Results
The 1st Tiny Object Detection (TOD) Challenge aims toencourage research ...
research
∙
08/10/2020
Prototype Mixture Models for Few-shot Semantic Segmentation
Few-shot segmentation is challenging because objects within the support ...
research
∙
08/05/2020
Component Divide-and-Conquer for Real-World Image Super-Resolution
In this paper, we present a large-scale Diverse Real-world image Super-R...
research
∙
07/27/2020
Learning Task-oriented Disentangled Representations for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims to address the domain-shift pr...
research
∙
07/07/2020
Discretization-Aware Architecture Search
The search cost of neural architecture search (NAS) has been largely red...
research
∙
07/06/2020
Progressive Cluster Purification for Unsupervised Feature Learning
In unsupervised feature learning, sample specificity based methods ignor...
research
∙
07/03/2020