5 papers
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset
Jinhong Wang, Shuo Tong, Jian liu +6
Visual rating is an essential capability of artificial intelligence (AI) for multi-dimensional quantification of visual content, primarily applied in ordinal regression (OR) tasks…
Dual-level Fuzzy Learning with Patch Guidance for Image Ordinal Regression
Chunlai Dong, Haochao Ying, Qibo Qiu +3
Ordinal regression bridges regression and classification by assigning objects to ordered classes. While human experts rely on discriminative patch-level features for decisions, cur…
OrderChain: Towards General Instruct-Tuning for Stimulating the Ordinal Understanding Ability of MLLM
Jinhong Wang, Shuo Tong, Jian liu +7
Despite the remarkable progress of multimodal large language models (MLLMs), they continue to face challenges in achieving competitive performance on ordinal regression (OR; a.k.a.…
A Survey on Ordinal Regression: Applications, Advances and Prospects
Jinhong Wang, Jintai Chen, Jian Liu +3
Ordinal regression refers to classifying object instances into ordinal categories. Ordinal regression is crucial for applications in various areas like facial age estimation, image…
Scalable Autoregressive Monocular Depth Estimation
Jinhong Wang, Jian Liu, Dongqi Tang +5
This paper shows that the autoregressive model is an effective and scalable monocular depth estimator. Our idea is simple: We tackle the monocular depth estimation (MDE) task with…