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Anis Kacem

12 accepted papers

2026

Cov2Pose: Leveraging Spatial Covariance for Direct Manifold-aware 6-DoF Object Pose Estimation

CVPR 2026

In this paper, we address the problem of 6-DoF object pose estimation from a single RGB image. Indirect methods that typically predict intermediate 2D keypoints, followed by a Perspective-n-Point solver, have shown great performance. Direct approaches, which regress the pose in an end-to-end manner,

Cited by 0SourceScholar
2025

CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers

ICCV 2025poster

We propose CAD-Assistant, a general-purpose CAD agent for AI-assisted design. Our approach is based on a powerful Vision and Large Language Model (VLLM) as a planner and a tool-augmentation paradigm using CAD-specific tools. CAD-Assistant addresses multimodal user queries by generating actions that…

2025

CAD-Recode: Reverse Engineering CAD Code from Point Clouds

ICCV 2025poster

Computer-Aided Design (CAD) models are typically constructed by sequentially drawing parametric sketches and applying CAD operations to obtain a 3D model. The problem of 3D CAD reverse engineering consists of reconstructing the sketch and CAD operation sequences from 3D representations such as point…

2025

Hybrid Attention for Robust RGB-T Pedestrian Detection in Real-World Conditions

RA-L 2025

Multispectral pedestrian detection has gained significant attention in recent years, particularly in autonomous driving applications. To address the challenges posed by adversarial illumination conditions, the combination of thermal and visible images has demonstrated its advantages. However, existi

Cited by 2SourceScholar
2025

MiCADangelo: Fine-Grained Reconstruction of Constrained CAD Models from 3D Scans

NeurIPS 2025poster

Computer-Aided Design (CAD) plays a foundational role in modern manufacturing and product development, often requiring designers to modify or build upon existing models. Converting 3D scans into parametric CAD representations—a process known as CAD reverse engineering—remains a significant challenge…

Cited by 0SourceScholar
2025

Uncertainty-Aware Knowledge Distillation for Compact and Efficient 6DoF Pose Estimation

IROS 2025

Compact and efficient 6DoF object pose estimation is crucial in applications such as robotics, augmented reality, and space autonomous navigation systems, where lightweight models are critical for real-time accurate performance. This paper introduces a novel uncertainty-aware end-to-end Knowledge Di

Cited by 2SourceScholar
2025

Vulnerability-Aware Spatio-Temporal Learning for Generalizable Deepfake Video Detection

ICCV 2025poster

Detecting deepfake videos is highly challenging given the complexity of characterizing spatio-temporal artifacts. Most existing methods rely on binary classifiers trained using real and fake image sequences, therefore hindering their generalization capabilities to unseen generation methods. Moreover…

2024

CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attention

CVPR 2024highlight

Reverse engineering in the realm of Computer-Aided Design (CAD) has been a longstanding aspiration though not yet entirely realized. Its primary aim is to uncover the CAD process behind a physical object given its 3D scan. We propose CAD-SIGNet an end-to-end trainable and auto-regressive architectur…

Cited by 18SourcePDFScholar
2024

LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection

CVPR 2024poster

This paper introduces a novel approach for high-quality deepfake detection called Localized Artifact Attention Network (LAA-Net). Existing methods for high-quality deepfake detection are mainly based on a supervised binary classifier coupled with an implicit attention mechanism. As a result they do…

2024

SpelsNet: Surface Primitive Elements Segmentation by B-Rep Graph Structure Supervision

NeurIPS 2024poster

Within the realm of Computer-Aided Design (CAD), Boundary-Representation (B-Rep) is the standard option for modeling shapes. We present SpelsNet, a neural architecture for the segmentation of 3D point clouds into surface primitive elements under topological supervision of its B-Rep graph structure.…

Cited by 1SourcePDFScholar
2024

TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Clouds

ECCV 2024poster

"3D reverse engineering, in which a CAD model is inferred given a 3D scan of a physical object, is a research direction that offers many promising practical applications. This paper proposes , an end-to-end transformer-based architecture that predicts the CAD sequence from a point cloud. leverages t…

Cited by 40SourcePDFScholar
2017

A Novel Space-Time Representation on the Positive Semidefinite Cone for Facial Expression Recognition

ICCV 2017poster

In this paper, we study the problem of facial expression recognition using a novel space-time geometric representation. We describe the temporal evolution of facial landmarks as parametrized trajectories on the Riemannian manifold of positive semidefinite matrices of fixed-rank. Our representation h…

Cited by 50PDFScholar