6 citations · 8 across the 9 of their papers we have counts for
9 papers · 1 filter
BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception
Geng Li, Yuxin Peng
While Multimodal Large Language Models (MLLMs) demonstrate impressive general capabilities, they struggle with fine-grained perception in ultra-high-resolution (UHR) images, partic…
LIMSSR: LLM-Driven Sequence-to-Score Reasoning under Training-Time Incomplete Multimodal Observations
Huangbiao Xu, Huanqi Wu, Xiao Ke +1
Real-world multimodal learning is often hindered by missing modalities. While Incomplete Multimodal Learning (IML) has gained traction, existing methods typically rely on the unrea…
CausalFSFG: Rethinking Few-Shot Fine-Grained Visual Categorization from Causal Perspective
Zhiwen Yang, Jinglin Xu, Yuxin Pen
Few-shot fine-grained visual categorization (FS-FGVC) focuses on identifying various subcategories within a common superclass given just one or few support examples. Most existing…
DyFo: A Training-Free Dynamic Focus Visual Search for Enhancing LMMs in Fine-Grained Visual Understanding
Geng Li, Jinglin Xu, Yunzhen Zhao +1
Humans can effortlessly locate desired objects in cluttered environments, relying on a cognitive mechanism known as visual search to efficiently filter out irrelevant information a…
Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models
Hulingxiao He, Geng Li, Zijun Geng +2
Multi-modal large language models (MLLMs) have shown remarkable abilities in various visual understanding tasks. However, MLLMs still struggle with fine-grained visual recognition…
CountMamba: Exploring Multi-directional Selective State-Space Models for Plant Counting
Hulingxiao He, Yaqi Zhang, Jinglin Xu +1
Plant counting is essential in every stage of agriculture, including seed breeding, germination, cultivation, fertilization, pollination yield estimation, and harvesting. Inspired…
SIA-OVD: Shape-Invariant Adapter for Bridging the Image-Region Gap in Open-Vocabulary Detection
Zishuo Wang, Wenhao Zhou, Jinglin Xu +1
Open-vocabulary detection (OVD) aims to detect novel objects without instance-level annotations to achieve open-world object detection at a lower cost. Existing OVD methods mainly…
FineParser: A Fine-grained Spatio-temporal Action Parser for Human-centric Action Quality Assessment
Jinglin Xu, Sibo Yin, Guohao Zhao +2
Existing action quality assessment (AQA) methods mainly learn deep representations at the video level for scoring diverse actions. Due to the lack of a fine-grained understanding o…
FinePOSE: Fine-Grained Prompt-Driven 3D Human Pose Estimation via Diffusion Models
Jinglin Xu, Yijie Guo, Yuxin Peng
The 3D Human Pose Estimation (3D HPE) task uses 2D images or videos to predict human joint coordinates in 3D space. Despite recent advancements in deep learning-based methods, they…