UNIC
General encoder for classification. Accompanies ECCV’24 paper.
Learning augmentation policies without prior knowledge.
A codebase to evaluate the robustness and uncertainty properties of semantic segmentation models as implemented in the CVPR 2024 paper.
Model for transfer learning.
Two ResNet50 models pretrained on our synthetic ImageNet clones: ImageNet-100-SD or ImageNet-1K-SD.
An Explicit Matching module for compatibility and an Implicit Similarity module for relevance.
Code for running our FIRe model , based solely on mid-level features that we call super-features.
A method that improves dense 2D image feature extractors when the latter are applied to the analysis of multiple images reconstructible as a 3D scene.
A Pytorch codebase for research to replicate the CVPR22 paper.
Official repo for the NeurIPS 2022 paper.
Dataset that allows exploration of cross-modal retrieval where images contain scene-text instances.
A method that is simple, easy to implement and train and of broad applicability.
Code repository for the ImageNet-CoG Benchmark introduced in the paper ICCV 2021 paper.
Data mixing strategies that can be computed on-the-fly with minimal computational overhead, highly transferable visual representations.
Repository contains models and evaluation scripts of papers ‘End-to-end Learning of Deep Visual Representations for Image Retrieval’ & ‘Learning with Average Precision: Training Image Retrieval with a Listwise Loss’.
