369 citations · 1.8k across the 93 of their papers we have counts for
83 papers · 1 filter
A Collaborative Multi-Modality Interaction for VLA-based End-to-End Autonomous Driving
Jingtao Sun, Xiaohai He, Yike Zhang +4
Vision-Language-Action (VLA) models have emerged as a powerful paradigm for end-to-end autonomous driving by jointly integrating perception, reasoning, and decision making within a…
SDFA: Structure Aware Discriminative Feature Aggregation for Efficient Human Fall Detection in Video
Sania Zahan, Ghulam Mubashar Hassan, Ajmal Mian
Older people are susceptible to fall due to instability in posture and deteriorating health. Immediate access to medical support can greatly reduce repercussions. Hence, there is a…
Modeling Human Skeleton Joint Dynamics for Fall Detection
Sania Zahan, Ghulam Mubashar Hassan, Ajmal Mian
The increasing pace of population aging calls for better care and support systems. Falling is a frequent and critical problem for elderly people causing serious long-term health is…
Multiview Point Cloud Registration Based on Minimum Potential Energy for Free-Form Blade Measurement
Zijie Wu, Yaonan Wang, Yang Mo +5
Point cloud registration is an essential step for free-form blade reconstruction in industrial measurement. Nonetheless, measuring defects of the 3D acquisition system unavoidably…
Diffusion-Driven Self-Supervised Learning for Shape Reconstruction and Pose Estimation
Jingtao Sun, Yaonan Wang, Mingtao Feng +3
Fully-supervised category-level pose estimation aims to determine the 6-DoF poses of unseen instances from known categories, requiring expensive mannual labeling costs. Recently, v…
Temporally Consistent Referring Video Object Segmentation with Hybrid Memory
Bo Miao, Mohammed Bennamoun, Yongsheng Gao +2
Referring Video Object Segmentation (R-VOS) methods face challenges in maintaining consistent object segmentation due to temporal context variability and the presence of other visu…
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation
Zijie Wu, Yaonan Wang, Mingtao Feng +2
Diffusion probabilistic models have achieved remarkable success in text guided image generation. However, generating 3D shapes is still challenging due to the lack of sufficient da…
Spectrum-guided Multi-granularity Referring Video Object Segmentation
Bo Miao, Mohammed Bennamoun, Yongsheng Gao +1
Current referring video object segmentation (R-VOS) techniques extract conditional kernels from encoded (low-resolution) vision-language features to segment the decoded high-resolu…
BAGM: A Backdoor Attack for Manipulating Text-to-Image Generative Models
Jordan Vice, Naveed Akhtar, Richard Hartley +1
The rise in popularity of text-to-image generative artificial intelligence (AI) has attracted widespread public interest. We demonstrate that this technology can be attacked to gen…
Human Gesture and Gait Analysis for Autism Detection
Sania Zahan, Zulqarnain Gilani, Ghulam Mubashar Hassan +1
Autism diagnosis presents a major challenge due to the vast heterogeneity of the condition and the elusive nature of early detection. Atypical gait and gesture patterns are dominan…
DANet: Density Adaptive Convolutional Network with Interactive Attention for 3D Point Clouds
Yong He, Hongshan Yu, Zhengeng Yang +3
Local features and contextual dependencies are crucial for 3D point cloud analysis. Many works have been devoted to designing better local convolutional kernels that exploit the co…
Full Point Encoding for Local Feature Aggregation in 3D Point Clouds
Yong He, Hongshan Yu, Zhengeng Yang +3
Point cloud processing methods exploit local point features and global context through aggregation which does not explicity model the internal correlations between local and global…
Learning Sparse Temporal Video Mapping for Action Quality Assessment in Floor Gymnastics
Sania Zahan, Ghulam Mubashar Hassan, Ajmal Mian
Athlete performance measurement in sports videos requires modeling long sequences since the entire spatio-temporal progression contributes dominantly to the performance. It is cruc…
Slice Transformer and Self-supervised Learning for 6DoF Localization in 3D Point Cloud Maps
Muhammad Ibrahim, Naveed Akhtar, Saeed Anwar +2
Precise localization is critical for autonomous vehicles. We present a self-supervised learning method that employs Transformers for the first time for the task of outdoor localiza…
Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition
Rohit Gupta, Naveed Akhtar, Gaurav Kumar Nayak +2
Black-box adversarial attacks present a realistic threat to action recognition systems. Existing black-box attacks follow either a query-based approach where an attack is optimized…
Simultaneous Multiple Object Detection and Pose Estimation using 3D Model Infusion with Monocular Vision
Congliang Li, Shijie Sun, Xiangyu Song +3
Multiple object detection and pose estimation are vital computer vision tasks. The latter relates to the former as a downstream problem in applications such as robotics and autonom…
3DMODT: Attention-Guided Affinities for Joint Detection & Tracking in 3D Point Clouds
Jyoti Kini, Ajmal Mian, Mubarak Shah
We propose a method for joint detection and tracking of multiple objects in 3D point clouds, a task conventionally treated as a two-step process comprising object detection followe…
Vision Transformer Based Model for Describing a Set of Images as a Story
Zainy M. Malakan, Ghulam Mubashar Hassan, Ajmal Mian
Visual Story-Telling is the process of forming a multi-sentence story from a set of images. Appropriately including visual variation and contextual information captured inside the…
Vision Transformers for Action Recognition: A Survey
Anwaar Ulhaq, Naveed Akhtar, Ganna Pogrebna +1
Vision transformers are emerging as a powerful tool to solve computer vision problems. Recent techniques have also proven the efficacy of transformers beyond the image domain to so…
Domain-invariant Prototypes for Semantic Segmentation
Zhengeng Yang, Hongshan Yu, Wei Sun +2
Deep Learning has greatly advanced the performance of semantic segmentation, however, its success relies on the availability of large amounts of annotated data for training. Hence,…
Region Aware Video Object Segmentation with Deep Motion Modeling
Bo Miao, Mohammed Bennamoun, Yongsheng Gao +1
Current semi-supervised video object segmentation (VOS) methods usually leverage the entire features of one frame to predict object masks and update memory. This introduces signifi…
Contrastive Self-Supervised Learning Leads to Higher Adversarial Susceptibility
Rohit Gupta, Naveed Akhtar, Ajmal Mian +1
Contrastive self-supervised learning (CSL) has managed to match or surpass the performance of supervised learning in image and video classification. However, it is still largely un…
Learning from Pixel-Level Noisy Label : A New Perspective for Light Field Saliency Detection
Mingtao Feng, Kendong Liu, Liang Zhang +3
Saliency detection with light field images is becoming attractive given the abundant cues available, however, this comes at the expense of large-scale pixel level annotated data wh…
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning
Nazmul Karim, Mamshad Nayeem Rizve, Nazanin Rahnavard +2
Supervised deep learning methods require a large repository of annotated data; hence, label noise is inevitable. Training with such noisy data negatively impacts the generalization…