Code & data

Code

• BiB: Active learning strategies for weakly-supervised object detection (ECCV’22)
• STEEX: Steering Counterfactual Explanations with Semantics (ECCV’22)
• CAB: Raising Context Awareness in Motion Forecasting (workshop CVPR’22)
• MuHDi: Multi-head distillation for continual unsupervised domain adaptation in semantic segmentation (CLVision’22)
• RADIal: HR radar dataset (+ camera & lidar) for vehicle and free space detection (CVPR’22)
• LOST: Object localization with self-supervised transformers (BMVC’21)
• MTAF: Multi-Target Adversarial Frameworks for domain adaptation (ICCV’21)
• MVRSS: Multi-view radar semantic segmentation (ICCV’21)
• ObsNet: Out-Of-Distribution detection by learning from local adversarial attacks in semantic segmentation (ICCV’21)
• Semantic Palette: Guiding scene generation with class proportions (CVPR’21)
• Attributes with Fields: Detecting 32 pedestrian attributes with composite fields (preprint’20 with EPFL)
• OBoW: Online BoW generation for unsupervised representation learning (CVPR 2021)
• DummyNet: Artificial Dummies for Urban Dataset Augmentation (AAAI’21)
• ESL: Entropy-guided Self-supervised Learning for Domain Adaptation in Semantic Segmentation (CVPRw’20)
• AdamSRT: Adam exploiting BN-induced pherical invariance of CNN (arXiv 2020)
• xMUDA: Cross-modal UDA for 3D semantic segmentation (CVPR’20)
• ZS3: Zero-Shot Semantic Segmentation (NeurIPS’19)
• BF3S: Boosting few-shot visual learning with self-supervision (ICCV’19)
• rOSD: Unsupervised object discovery at scale (ECCV’20) - Matlab
• ConfidNet: Addressing failure prediction by learning model confidence (NeurIPS’19) - PyTorch
• DADA: Depth-aware Domain Adaptation in Semantic Segmentation (ICCV’19) - coming soon
• AdvEnt: Adversarial Entropy minimization for domain adaptation in semantic segmentation (CVPR’19) - PyTorch
• SoDeep: Sorting Deep Net to learn ranking loss surrogates (CVP’19) - PyTorch
• OSD: Unsupervised object discovery as optimization (CVPR’19) - Matlab
• DSVE-loc: Deep Semantic Visual Embedding with Localization (CVPR’18) - PyTorch
• SuBic: Supervised Binary Codes (ICCV’17) - Python
• ROAM: Rich Online Appearance Model (CPVR’17) - C++, using OpenCV 3.0
• SLEM: Square Loss Exemplar Machines (CVPR’17) - Matlab
• VLAD: Vector of Locally Aggregated Descriptors (CVPR’10) - Matlab, using Yael
• VideoInpaint: Patch-based video inpainting (SIAM J. Imaging Science 2014) - Matlab

Data

• Woodscape: Driving fisheye multi-task dataset
• CARRADA: Camera and Automotive Radar with Range-Angle-Doppler Annotations dataset
• TSFT: Face tubes from TV series (589 cropped annotated face tubes of 94 subjects)
• Hannah: Dense person annotation of Woody Allen’s Hannah and her sisters
• Scratch: Annotated data on scractch detection for movie restoration
• VideoInpainting: Videos and objects’ masks for object inpainting