activity
20222025
most citedFusionCount: Efficient Crowd Counting via Multiscale Feature Fusion

36 citations · 67 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2025

UniMPR: A Unified Framework for Multimodal Place Recognition with Heterogeneous Sensor Configurations

Zhangshuo Qi, Jingyi Xu, Luqi Cheng +3

Place recognition is a critical component of autonomous vehicles and robotics, enabling global localization in GPS-denied environments. Recent advances have spurred significant int…

cs.CV2025

ZIP: Scalable Crowd Counting via Zero-Inflated Poisson Modeling

Yiming Ma, Victor Sanchez, Tanaya Guha

Most crowd counting methods directly regress blockwise density maps using Mean Squared Error (MSE) losses. This practice has two key limitations: (1) it fails to account for the ex…

eess.IV2025

SLENet: A Novel Multiscale CNN-Based Network for Detecting the Rats Estrous Cycle

Qinyang Wang, Hoileong Lee, Xiaodi Pu +2

In clinical medicine, rats are commonly used as experimental subjects. However, their estrous cycle significantly impacts their biological responses, leading to differences in expe…

cs.CV2024

Interact with me: Joint Egocentric Forecasting of Intent to Interact, Attitude and Social Actions

Tongfei Bian, Yiming Ma, Mathieu Chollet +2

For efficient human-agent interaction, an agent should proactively recognize their target user and prepare for upcoming interactions. We formulate this challenging problem as the n…

cs.LG2024

PuYun: Medium-Range Global Weather Forecasting Using Large Kernel Attention Convolutional Networks

Shengchen Zhu, Yiming Chen, Peiying Yu +7

Accurate weather forecasting is essential for understanding and mitigating weather-related impacts. In this paper, we present PuYun, an autoregressive cascade model that leverages…

cs.CV2024

MDPE: A Multimodal Deception Dataset with Personality and Emotional Characteristics

Cong Cai, Shan Liang, Xuefei Liu +11

Deception detection has garnered increasing attention in recent years due to the significant growth of digital media and heightened ethical and security concerns. It has been exten…

cs.CV2024★ 9 cited

CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification

Yiming Ma, Victor Sanchez, Tanaya Guha

We propose CLIP-EBC, the first fully CLIP-based model for accurate crowd density estimation. While the CLIP model has demonstrated remarkable success in addressing recognition task…

cs.CV2023★ 15 cited

Robust Multiview Multimodal Driver Monitoring System Using Masked Multi-Head Self-Attention

Yiming Ma, Victor Sanchez, Soodeh Nikan +3

Driver Monitoring Systems (DMSs) are crucial for safe hand-over actions in Level-2+ self-driving vehicles. State-of-the-art DMSs leverage multiple sensors mounted at different loca…

cs.CV2022★ 3 cited

Inception-Based Crowd Counting -- Being Fast while Remaining Accurate

Yiming Ma

Recent sophisticated CNN-based algorithms have demonstrated their extraordinary ability to automate counting crowds from images, thanks to their structures which are designed to ad…

cs.CV2022★ 4 cited

Real-Time Driver Monitoring Systems through Modality and View Analysis

Yiming Ma, Victor Sanchez, Soodeh Nikan +3

Driver distractions are known to be the dominant cause of road accidents. While monitoring systems can detect non-driving-related activities and facilitate reducing the risks, they…

cs.CV2022★ 36 cited

FusionCount: Efficient Crowd Counting via Multiscale Feature Fusion

Yiming Ma, Victor Sanchez, Tanaya Guha

State-of-the-art crowd counting models follow an encoder-decoder approach. Images are first processed by the encoder to extract features. Then, to account for perspective distortio…