research
∙
06/15/2023
OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection
Out-of-Distribution (OOD) detection is critical for the reliable operati...
share
research
∙
05/29/2023
Contextual Object Detection with Multimodal Large Language Models
Recent Multimodal Large Language Models (MLLMs) are remarkable in vision...
research
∙
05/24/2023
Semi-Supervised and Long-Tailed Object Detection with CascadeMatch
This paper focuses on long-tailed object detection in the semi-supervise...
research
∙
01/31/2023
What Makes Good Examples for Visual In-Context Learning?
Large-scale models trained on broad data have recently become the mainst...
research
∙
10/25/2022
Learning to Augment via Implicit Differentiation for Domain Generalization
Machine learning models are intrinsically vulnerable to domain shift bet...
research
∙
10/13/2022
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
Out-of-distribution (OOD) detection is vital to safety-critical machine ...
research
∙
10/13/2022
Unified Vision and Language Prompt Learning
Prompt tuning, a parameter- and data-efficient transfer learning paradig...
research
∙
09/15/2022
On-Device Domain Generalization
We present a systematic study of domain generalization (DG) for tiny neu...
research
∙
07/22/2022
Panoptic Scene Graph Generation
Existing research addresses scene graph generation (SGG) – a critical te...
research
∙
07/17/2022
Detecting Humans in RGB-D Data with CNNs
We address the problem of people detection in RGB-D data where we levera...
research
∙
06/09/2022
Neural Prompt Search
The size of vision models has grown exponentially over the last few year...
research
∙
04/11/2022
Full-Spectrum Out-of-Distribution Detection
Existing out-of-distribution (OOD) detection literature clearly defines ...
research
∙
03/22/2022
Open-Vocabulary DETR with Conditional Matching
Open-vocabulary object detection, which is concerned with the problem of...
research
∙
03/10/2022
Conditional Prompt Learning for Vision-Language Models
With the rise of powerful pre-trained vision-language models like CLIP, ...
research
∙
03/09/2022
Dynamic Instance Domain Adaptation
Most existing studies on unsupervised domain adaptation (UDA) assume tha...
research
∙
11/06/2021
Domain Attention Consistency for Multi-Source Domain Adaptation
Most existing multi-source domain adaptation (MSDA) methods minimize the...
research
∙
10/21/2021
Generalized Out-of-Distribution Detection: A Survey
Out-of-distribution (OOD) detection is critical to ensuring the reliabil...
research
∙
09/02/2021
Learning to Prompt for Vision-Language Models
Vision-language pre-training has recently emerged as a promising alterna...
research
∙
07/27/2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Confidence calibration is of great importance to the reliability of deci...
research
∙
07/05/2021
MixStyle Neural Networks for Domain Generalization and Adaptation
Convolutional neural networks (CNNs) often have poor generalization perf...
research
∙
06/01/2021
Semi-Supervised Domain Generalization with Stochastic StyleMatch
Most existing research on domain generalization assumes source data gath...
research
∙
04/05/2021
Domain Generalization with MixStyle
Though convolutional neural networks (CNNs) have demonstrated remarkable...
research
∙
03/03/2021
Domain Generalization: A Survey
Generalization to out-of-distribution (OOD) data is a capability natural...
research
∙
07/07/2020
Learning to Generate Novel Domains for Domain Generalization
This paper focuses on domain generalization (DG), the task of learning f...
research
∙
03/16/2020
Domain Adaptive Ensemble Learning
The problem of generalizing deep neural networks from multiple source do...
research
∙
03/12/2020
Deep Domain-Adversarial Image Generation for Domain Generalisation
Machine learning models typically suffer from the domain shift problem w...
research
∙
10/22/2019
Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch
Person re-identification (re-ID), which aims to re-identify people acros...
research
∙
10/15/2019
Learning Generalisable Omni-Scale Representations for Person Re-Identification
An effective person re-identification (re-ID) model should learn feature...
research
∙
05/02/2019
Omni-Scale Feature Learning for Person Re-Identification
As an instance-level recognition problem, person re-identification (ReID...
research
∙
07/09/2018
Video Summarisation by Classification with Deep Reinforcement Learning
Most existing video summarisation methods are based on either supervised...
research
∙
12/29/2017
