6 citations · 14 across the 9 of their papers we have counts for
9 papers
Category-Extensible Out-of-Distribution Detection via Hierarchical Context Descriptions
Kai Liu, Zhihang Fu, Chao Chen +5
The key to OOD detection has two aspects: generalized feature representation and precise category description. Recently, vision-language models such as CLIP provide significant adv…
Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection
Chao Chen, Zhihang Fu, Kai Liu +3
For a machine learning model deployed in real world scenarios, the ability of detecting out-of-distribution (OOD) samples is indispensable and challenging. Most existing OOD detect…
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection
Chao Chen, Kai Liu, Ze Chen +5
Knowledge hallucination have raised widespread concerns for the security and reliability of deployed LLMs. Previous efforts in detecting hallucinations have been employed at logit-…
ChangeNet: Multi-Temporal Asymmetric Change Detection Dataset
Deyi Ji, Siqi Gao, Mingyuan Tao +2
Change Detection (CD) has been attracting extensive interests with the availability of bi-temporal datasets. However, due to the huge cost of multi-temporal images acquisition and…
Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark
Deyi Ji, Feng Zhao, Hongtao Lu +2
With the increasing interest and rapid development of methods for Ultra-High Resolution (UHR) segmentation, a large-scale benchmark covering a wide range of scenes with full fine-g…
Structural and Statistical Texture Knowledge Distillation for Semantic Segmentation
Deyi Ji, Haoran Wang, Mingyuan Tao +3
Existing knowledge distillation works for semantic segmentation mainly focus on transferring high-level contextual knowledge from teacher to student. However, low-level texture kno…
Invariant Feature Learning for Generalized Long-Tailed Classification
Kaihua Tang, Mingyuan Tao, Jiaxin Qi +2
Existing long-tailed classification (LT) methods only focus on tackling the class-wise imbalance that head classes have more samples than tail classes, but overlook the attribute-w…
Spatial Likelihood Voting with Self-Knowledge Distillation for Weakly Supervised Object Detection
Ze Chen, Zhihang Fu, Jianqiang Huang +5
Weakly supervised object detection (WSOD), which is an effective way to train an object detection model using only image-level annotations, has attracted considerable attention fro…
Dynamic Supervisor for Cross-dataset Object Detection
Ze Chen, Zhihang Fu, Jianqiang Huang +6
The application of cross-dataset training in object detection tasks is complicated because the inconsistency in the category range across datasets transforms fully supervised learn…