2 citations · 7 across the 42 of their papers we have counts for
17 papers · 1 filter
Explainable Action Form Assessment by Exploiting Multimodal Chain-of-Thoughts Reasoning
Mengshi Qi, Yeteng Wu, Wulian Yun +2
Evaluating whether human action is standard or not and providing reasonable feedback to improve action standardization is very crucial but challenging in real-world scenarios. Howe…
RoboDriveVLM: A Novel Benchmark and Baseline towards Robust Vision-Language Models for Autonomous Driving
Dacheng Liao, Mengshi Qi, Peng Shu +4
Current Vision-Language Model (VLM)-based end-to-end autonomous driving systems often leverage large language models to generate driving decisions directly based on their understan…
Multi-Modal Scene Graph with Kolmogorov-Arnold Experts for Audio-Visual Question Answering
Zijian Fu, Changsheng Lv, Xianlin Zhang +2
In this paper, we propose a novel Multi-Modal Scene Graph with Kolmogorov-Arnold Expert Network for Audio-Visual Question Answering (SHRIKE). The task aims to mimic human reasoning…
Synergistic Tensor and Pipeline Parallelism
Mengshi Qi, Jiaxuan Peng, Jie Zhang +3
In the machine learning system, the hybrid model parallelism combining tensor parallelism (TP) and pipeline parallelism (PP) has become the dominant solution for distributed traini…
SoccerNet 2025 Challenges Results
Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115
The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…
SafeDriveRAG: Towards Safe Autonomous Driving with Knowledge Graph-based Retrieval-Augmented Generation
Hao Ye, Mengshi Qi, Zhaohong Liu +2
In this work, we study how vision-language models (VLMs) can be utilized to enhance the safety for the autonomous driving system, including perception, situational understanding, a…
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
Mengshi Qi, Pengfei Zhu, Xiangtai Li +4
Given a single labeled example, in-context segmentation aims to segment corresponding objects. This setting, known as one-shot segmentation in few-shot learning, explores the segme…
Chain-of-Evidence Multimodal Reasoning for Few-shot Temporal Action Localization
Mengshi Qi, Hongwei Ji, Wulian Yun +2
Traditional temporal action localization (TAL) methods rely on large amounts of detailed annotated data, whereas few-shot TAL reduces this dependence by using only a few training s…
Global-Local Tree Search in VLMs for 3D Indoor Scene Generation
Wei Deng, Mengshi Qi, Huadong Ma
Large Vision-Language Models (VLMs), such as GPT-4, have achieved remarkable success across various fields. However, there are few studies on 3D indoor scene generation with VLMs.…
Robust Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning
Mengshi Qi, Changsheng Lv, Huadong Ma
In this paper, we propose a new Robust Disentangled Counterfactual Learning (RDCL) approach for physical audiovisual commonsense reasoning. The task aims to infer objects' physics…
VLM-Assisted Continual learning for Visual Question Answering in Self-Driving
Yuxin Lin, Mengshi Qi, Liang Liu +1
In this paper, we propose a novel approach for solving the Visual Question Answering (VQA) task in autonomous driving by integrating Vision-Language Models (VLMs) with continual le…
Towards Robust Unsupervised Attention Prediction in Autonomous Driving
Mengshi Qi, Xiaoyang Bi, Pengfei Zhu +1
Robustly predicting attention regions of interest for self-driving systems is crucial for driving safety but presents significant challenges due to the labor-intensive nature of ob…
A New Teacher-Reviewer-Student Framework for Semi-supervised 2D Human Pose Estimation
Wulian Yun, Mengshi Qi, Fei Peng +1
Conventional 2D human pose estimation methods typically require extensive labeled annotations, which are both labor-intensive and expensive. In contrast, semi-supervised 2D human p…
Human Grasp Generation for Rigid and Deformable Objects with Decomposed VQ-VAE
Mengshi Qi, Zhe Zhao, Huadong Ma
Generating realistic human grasps is crucial yet challenging for object manipulation in computer graphics and robotics. Current methods often struggle to generate detailed and real…
Improving Partially Observed Trajectories Forecasting by Target-driven Self-Distillation
Peng Shu, Pengfei Zhu, Mengshi Qi +1
Accurate prediction of future trajectories of traffic agents is essential for ensuring safe autonomous driving. However, partially observed trajectories can significantly degrade t…
Towards Balanced Multi-Modal Learning in 3D Human Pose Estimation
Mengshi Qi, Jiaxuan Peng, Xianlin Zhang +1
3D human pose estimation (3D HPE) has emerged as a prominent research topic, particularly in the realm of RGB-based methods. However, the use of RGB images is often limited by issu…
Action Quality Assessment via Hierarchical Pose-guided Multi-stage Contrastive Regression
Mengshi Qi, Hao Ye, Jiaxuan Peng +1
Action Quality Assessment (AQA), which aims at automatic and fair evaluation of athletic performance, has gained increasing attention in recent years. However, athletes are often i…