"Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions. (arXiv:2209.13603v3 [cs.CV] UPDATED)" — A hybrid discrete-continuous (DISCO) group convolution for spherical convolutional neural networks (CNN) that is simultaneously equivariant and computationally scalable to high-resolution.

Paper: http://arxiv.org/abs/2209.13603

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Spherical CNN categorization

"Multi-Level Visual Similarity Based Personalized Tourist Attraction Recommendation Using Geo-Tagged Photos. (arXiv:2109.08275v2 [cs.MM] UPDATED)" — A geo-tagged photo based tourist attraction recommendation system which utilizes the visual contents of photos and interaction behavior data to obtain the final embeddings of users and tourist attractions, which are then used to predict the visit probabilities.

Paper: http://arxiv.org/abs/2109.08275
Code: https://github.com/revaludo/MEAL

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An illustration of the multi-le…

"BiAdam: Fast Adaptive Bilevel Optimization Methods. (arXiv:2106.11396v3 [math.OC] UPDATED)" — A novel fast adaptive bilevel framework to solve stochastic bilevel optimization problems that the outer problem is possibly nonconvex and the inner problem is strongly convex.

Paper: http://arxiv.org/abs/2106.11396

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The basic idea of the convergen…

"Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features. (arXiv:2104.02922v2 [cs.LG] UPDATED)" — An effort to understanding which of the internal features computed by the neural net are responsible for a particular class, by mimicking part of the neural net with an oblique decision tree having sparse weight vectors at the decision nodes.

Paper: http://arxiv.org/abs/2104.02922

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Mimicking part of a neural net …

"Don't Play Favorites: Minority Guidance for Diffusion Models. (arXiv:2301.12334v1 [cs.LG])" — A framework that can make the generation process of the diffusion models focus on the minority samples, which are instances that lie on low-density regions of a data manifold.

Paper: http://arxiv.org/abs/2301.12334

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Diffusion models play favorites…

"SEGA: Instructing Diffusion using Semantic Dimensions. (arXiv:2301.12247v1 [cs.CV])" — A semantic guidance method for diffusion models to allow making subtle and extensive edits and changes in composition and style, as well as optimize the overall artistic conception.

Paper: http://arxiv.org/abs/2301.12247

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Semantic control over image gen…

"Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits. (arXiv:2301.12168v1 [cs.LG])" — A new training technique based on weighted ensembles of early exits, which aims at exploiting the information in the structure of networks to maximise their performance.

Paper: http://arxiv.org/abs/2301.12168

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Outline of the AEP technique. O…

"ClusterFuG: Clustering Fully connected Graphs by Multicut. (arXiv:2301.12159v1 [cs.CV])" — A simpler and potentially better performing graph clustering formulation based on multicut (a.k.a. weighted correlation clustering) on the complete graph.

Paper: http://arxiv.org/abs/2301.12159

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Example illustration of dense m…

"Towards Equitable Representation in Text-to-Image Synthesis Models with the Cross-Cultural Understanding Benchmark (CCUB) Dataset. (arXiv:2301.12073v1 [cs.CV])" — A culturally-aware priming approach for text-to-image synthesis using a small but culturally curated dataset to fight the bias prevalent in giant datasets.

Paper: http://arxiv.org/abs/2301.12073

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Sample images generated for fiv…

"Cross-Architectural Positive Pairs improve the effectiveness of Self-Supervised Learning. (arXiv:2301.12025v1 [cs.CV])" — A novel self-supervised learning approach that leverages Transformer and CNN simultaneously to overcome the issues with existing self-supervised techniques which have extreme computational requirements and suffer a substantial drop in performance with a reduction in batch size or pretraining epochs.

Paper: http://arxiv.org/abs/2301.12025

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In our proposed self-supervised…

"Improved knowledge distillation by utilizing backward pass knowledge in neural networks. (arXiv:2301.12006v1 [cs.LG])" — Addressing the issue with Knowledge Distillation (KD) where there is no guarantee that the model would match in areas for which you do not have enough training samples, by generating new auxiliary training samples based on extracting knowledge from the backward pass of the teacher in the areas where the student diverges greatly from the teacher.

Paper: http://arxiv.org/abs/2301.12006

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a) Minimization Step: Using the…

"RGB Arabic Alphabets Sign Language Dataset. (arXiv:2301.11932v1 [cs.CV])" — An Arabic Alphabet Sign Language (AASL) dataset comprising of 7,856 raw and fully labelled RGB images of the Arabic sign language alphabets which might be the first such publicly available dataset.

Paper: http://arxiv.org/abs/2301.11932

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Sample images from the dataset

"Input Perturbation Reduces Exposure Bias in Diffusion Models. (arXiv:2301.11706v1 [cs.LG])" — An exploration of the fact that the the long sampling chain in Denoising Diffusion Probabilistic Models (DDPM) leads to an error accumulation phenomenon, which is similar to the exposure bias problem in autoregressive text generation.

Paper: http://arxiv.org/abs/2301.11706

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The inputs and the prediction t…

"Image Restoration with Mean-Reverting Stochastic Differential Equations. (arXiv:2301.11699v1 [cs.LG])" — A stochastic differential equation (SDE) approach for general-purpose image restoration which can restore images without relying on any task-specific prior knowledge.

Paper: http://arxiv.org/abs/2301.11699

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An overview of our proposed con…

"Accelerating Guided Diffusion Sampling with Splitting Numerical Methods. (arXiv:2301.11558v1 [cs.CV])" — A solution to speeding up guided diffusion image generation based on operator splitting methods, motivated by the finding that classical high-order numerical methods are unsuitable for the conditional function.

Paper: http://arxiv.org/abs/2301.11558

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Generated samples of a classifi…

"3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models. (arXiv:2301.11445v1 [cs.CV])" — A novel shape representation for neural fields designed for generative diffusion models, which can encode 3D shapes given as surface models or point clouds, and represents them as neural fields.

Paper: http://arxiv.org/abs/2301.11445

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Left: Shape autoencoding result…

"Improving Cross-modal Alignment for Text-Guided Image Inpainting. (arXiv:2301.11362v1 [cs.CV])" — A model for text-guided image inpainting by improving cross-modal alignment (CMA) using cross-modal alignment distillation and in-sample distribution distillation.

Paper: http://arxiv.org/abs/2301.11362

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Different categories of vision-…

"Rethinking 1x1 Convolutions: Can we train CNNs with Frozen Random Filters?. (arXiv:2301.11360v1 [cs.CV])" — An exploration into whether Convolutional Neural Networks (CNN) learning the weights of vast numbers of convolutional operators is really necessary.

Paper: http://arxiv.org/abs/2301.11360

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Validation accuracy of LCResNet…

"Multimodal Event Transformer for Image-guided Story Ending Generation. (arXiv:2301.11357v1 [cs.CV])" — A multimodal event transformer, an event-based reasoning framework for image-guided story ending generation which constructs visual and semantic event graphs from story plots and ending image, and leverages event-based reasoning to reason and mine implicit information in a single modality.

Paper: http://arxiv.org/abs/2301.11357

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Given a multi-sentence story pl…

"Animating Still Images. (arXiv:2209.10497v2 [cs.CV] UPDATED)" — A method for imparting motion to a still 2D image which uses deep learning to segment part of the image as the subject, uses in-paining to complete the background, and then adds animation to the subject.

Paper: http://arxiv.org/abs/2209.10497

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Interactive segmentation: Green…