119 citations · 552 across the 37 of their papers we have counts for
42 papers
NeuroSymbEAD: A Large Scale Neuro-Symbolic Caption Dataset for Omni-Directional Embodied Autonomous Driving
Muhammad Ahmed Ullah Khan, Mohammed Elamine, Sheikh Talha Uddin +3
This paper introduces NeuroSymbEAD, a large-scale neuro-symbolic caption dataset featuring an ego-centric knowledge graph (KG) of static and dynamic objects annotated with classes,…
BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understanding
Muhammad Usama, Didier Stricker, Mohammad Sadil Khan +1
Learning representations of CAD models is a largely open problem. While 3D representation learning has flourished around point clouds and meshes, the native format of CAD - boundar…
VVitCutLER: Towards Unsupervised Object Detection and Segmentation in Videos
Zhijing Lu, Khurram Azeem Hashmi, Didier Stricker +1
Unsupervised pixel-level video understanding remains challenging in real-world scenarios, where motion blur, occlusion, and fast object dynamics often cause temporal drift and flic…
ReConText3D: Replay-based Continual Text-to-3D Generation
Muhammad Ahmed Ullah Khan, Muhammad Haris Bin Amir, Didier Stricker +1
Continual learning enables models to acquire new knowledge over time while retaining previously learned capabilities. However, its application to text-to-3D generation remains unex…
DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces
Mohammad Sadil Khan, Muhammad Usama, Rolandos Alexandros Potamias +4
Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets with explicit d…
NURBGen: High-Fidelity Text-to-CAD Generation through LLM-Driven NURBS Modeling
Muhammad Usama, Mohammad Sadil Khan, Didier Stricker +1
Generating editable 3D CAD models from natural language remains challenging, as existing text-to-CAD systems either produce meshes or rely on scarce design-history data. We present…
Beyond Boxes: Mask-Guided Spatio-Temporal Feature Aggregation for Video Object Detection
Khurram Azeem Hashmi, Talha Uddin Sheikh, Didier Stricker +1
The primary challenge in Video Object Detection (VOD) is effectively exploiting temporal information to enhance object representations. Traditional strategies, such as aggregating…
MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation
Sankalp Sinha, Mohammad Sadil Khan, Muhammad Usama +4
Generating high-fidelity 3D content from text prompts remains a significant challenge in computer vision due to the limited size, diversity, and annotation depth of the existing da…
Text2CAD: Generating Sequential CAD Models from Beginner-to-Expert Level Text Prompts
Mohammad Sadil Khan, Sankalp Sinha, Talha Uddin Sheikh +3
Prototyping complex computer-aided design (CAD) models in modern softwares can be very time-consuming. This is due to the lack of intelligent systems that can quickly generate simp…
Classroom-Inspired Multi-Mentor Distillation with Adaptive Learning Strategies
Shalini Sarode, Muhammad Saif Ullah Khan, Tahira Shehzadi +2
We propose ClassroomKD, a novel multi-mentor knowledge distillation framework inspired by classroom environments to enhance knowledge transfer between the student and multiple ment…
Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformer
Tahira Shehzadi, Ifza, Didier Stricker +1
The impressive advancements in semi-supervised learning have driven researchers to explore its potential in object detection tasks within the field of computer vision. Semi-Supervi…
Enhanced Bank Check Security: Introducing a Novel Dataset and Transformer-Based Approach for Detection and Verification
Muhammad Saif Ullah Khan, Tahira Shehzadi, Rabeya Noor +2
Automated signature verification on bank checks is critical for fraud prevention and ensuring transaction authenticity. This task is challenging due to the coexistence of signature…
UnSupDLA: Towards Unsupervised Document Layout Analysis
Talha Uddin Sheikh, Tahira Shehzadi, Khurram Azeem Hashmi +2
Document layout analysis is a key area in document research, involving techniques like text mining and visual analysis. Despite various methods developed to tackle layout analysis,…
Shape2.5D: A Dataset of Texture-less Surfaces for Depth and Normals Estimation
Muhammad Saif Ullah Khan, Sankalp Sinha, Didier Stricker +2
Reconstructing texture-less surfaces poses unique challenges in computer vision, primarily due to the lack of specialized datasets that cater to the nuanced needs of depth and norm…
SituationalLLM: Proactive language models with scene awareness for dynamic, contextual task guidance
Muhammad Saif Ullah Khan, Muhammad Zeshan Afzal, Didier Stricker
Large language models (LLMs) have achieved remarkable success in text-based tasks but often struggle to provide actionable guidance in real-world physical environments. This is bec…
Estimating Human Poses Across Datasets: A Unified Skeleton and Multi-Teacher Distillation Approach
Muhammad Saif Ullah Khan, Dhavalkumar Limbachiya, Didier Stricker +1
Human pose estimation is a key task in computer vision with various applications such as activity recognition and interactive systems. However, the lack of consistency in the annot…
End-to-End Semi-Supervised approach with Modulated Object Queries for Table Detection in Documents
Iqraa Ehsan, Tahira Shehzadi, Didier Stricker +1
Table detection, a pivotal task in document analysis, aims to precisely recognize and locate tables within document images. Although deep learning has shown remarkable progress in…
CICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification
Sankalp Sinha, Muhammad Saif Ullah Khan, Talha Uddin Sheikh +2
Zero-shot learning has been extensively investigated in the broader field of visual recognition, attracting significant interest recently. However, the current work on zero-shot le…
Towards End-to-End Semi-Supervised Table Detection with Semantic Aligned Matching Transformer
Tahira Shehzadi, Shalini Sarode, Didier Stricker +1
Table detection within document images is a crucial task in document processing, involving the identification and localization of tables. Recent strides in deep learning have subst…
A Hybrid Approach for Document Layout Analysis in Document images
Tahira Shehzadi, Didier Stricker, Muhammad Zeshan Afzal
Document layout analysis involves understanding the arrangement of elements within a document. This paper navigates the complexities of understanding various elements within docume…
Sparse Semi-DETR: Sparse Learnable Queries for Semi-Supervised Object Detection
Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker +1
In this paper, we address the limitations of the DETR-based semi-supervised object detection (SSOD) framework, particularly focusing on the challenges posed by the quality of objec…
Human Pose Descriptions and Subject-Focused Attention for Improved Zero-Shot Transfer in Human-Centric Classification Tasks
Muhammad Saif Ullah Khan, Muhammad Ferjad Naeem, Federico Tombari +3
We present a novel LLM-based pipeline for creating contextual descriptions of human body poses in images using only auxiliary attributes. This approach facilitates the creation of…
Introducing Language Guidance in Prompt-based Continual Learning
Muhammad Gul Zain Ali Khan, Muhammad Ferjad Naeem, Luc Van Gool +3
Continual Learning aims to learn a single model on a sequence of tasks without having access to data from previous tasks. The biggest challenge in the domain still remains catastro…
Object Detection with Transformers: A Review
Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker +1
The astounding performance of transformers in natural language processing (NLP) has motivated researchers to explore their applications in computer vision tasks. DEtection TRansfor…