6 citations · 8 across the 12 of their papers we have counts for
14 papers
Understanding NVIDIA Grace-Blackwell Unified Memory Through Placement-Controlled Microbenchmarks
Nathan Graddon, Aaron Jarmusch, Sunita Chandrasekaran
NVIDIA Grace--Blackwell systems make CPU--GPU memory increasingly unified at the programming level, but unified addressability does not make the memory system uniform. A CUDA manag…
GeoAnchor: Collaborative Reasoning via Latent Decomposition for 3D Spatial Understanding
Hao Li, Han Fang, Zixin Pan +8
Although multimodal large language models (MLLMs) have achieved remarkable progress, understanding 3D spatial relationships from 2D images remains a critical challenge. Existing me…
Mixture-of-Thought-Tokens: Unifying Perception and Reasoning for Free-form Multimodal Grounding
Tianyi Gao, Han Fang, Tianyi Ding +9
Multimodal Large Language Models have made great progress in grounding tasks, yet existing methods still struggle to unify precise localization and complex reasoning. For one thing…
MoAKE: Toward Unified All-in-One Action Quality Assessment via Mixture of Action Knowledge Experts
Huangbiao Xu, Huanqi Wu, Xiao Ke +3
Action Quality Assessment (AQA) aims to objectively evaluate performance quality from action videos. Most existing methods follow a ``one-by-one'' paradigm, training a separate mod…
IPSM-Bench: A New Intermediate Phase Segmentation Benchmark in Microstructure Images of Zinc-Based Absorbable Biomaterials
Jinglin Xu, Shangyan Zhao, Jiabo Wang +5
Zinc-based alloys are indispensable emerging absorbable metallic biomaterials, and their macroscopic performance is governed by microstructural characteristics. Intermediate phases…
Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration
Jinglin Xu, Yi Li, Chuxiong Sun +3
Multi-modal test-time adaptation (TTA) enhances the resilience of benchmark multi-modal models against distribution shifts by leveraging the unlabeled target data during inference.…
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…
RefBench-PRO: Perceptual and Reasoning Oriented Benchmark for Referring Expression Comprehension
Tianyi Gao, Hao Li, Han Fang +8
Referring Expression Comprehension (REC) is a vision-language task that localizes a specific image region based on a textual description. Existing REC benchmarks primarily evaluate…
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…