7 papers
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…
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…
PoseAdapt: Sustainable Human Pose Estimation via Continual Learning Benchmarks and Toolkit
Muhammad Saif Ullah Khan, Didier Stricker
Human pose estimators are typically retrained from scratch or naively fine-tuned whenever keypoint sets, sensing modalities, or deployment domains change--an inefficient, compute-i…
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…
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…
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…