"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…

"VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media. (arXiv:2208.09021v3 [cs.CV] UPDATED)" — An extension of the popular Vision-and-Language Transformer (ViLT) to improve performance on vision-and-language (VL) tasks that involve more complex text inputs than image captions while having minimal impact on training and inference efficiency.

Paper: http://arxiv.org/abs/2208.09021
Code: https://github.com/gchochla/vault

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VAuLT propagates representation…

"SIViDet: Salient Image for Efficient Weaponized Violence Detection. (arXiv:2207.12850v4 [cs.CV] UPDATED)" — A new dataset that contains videos depicting weaponized violence, non-weaponized violence, and non-violent events; and a proposal for a novel data-centric method that arranges video frames into salient images while minimizing information loss for comfortable inference by SOTA image classifiers.

Paper: http://arxiv.org/abs/2207.12850
Code: https://github.com/Ti-Oluwanimi/Violence_Detection

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Salient Image: A sequence of vi…

"BridgeTower: Building Bridges Between Encoders in Vision-Language Representation Learning. (arXiv:2206.08657v3 [cs.CV] UPDATED)" — A proposal for multiple bridge layers that build a connection between the top layers of uni-modal encoders and each layer of the cross-modal encoder.

Paper: http://arxiv.org/abs/2206.08657
Code: https://github.com/microsoft/BridgeTower

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(a) – (d) are four categories o…

"Text-To-4D Dynamic Scene Generation. (arXiv:2301.11280v1 [cs.CV])" — A method for generating three-dimensional dynamic scenes from text descriptions which uses a 4D dynamic Neural Radiance Field (NeRF), which is optimized for scene appearance, density, and motion consistency by querying a Text-to-Video (T2V) diffusion-based model.

Paper: http://arxiv.org/abs/2301.11280

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Samples generated by MAV3D alon…

"BiBench: Benchmarking and Analyzing Network Binarization. (arXiv:2301.11233v1 [cs.CV])" — A rigorously designed benchmark with in-depth analysis for network binarization where they scrutinize the requirements of binarization in the actual production and define evaluation tracks and metrics for a comprehensive investigation.

Paper: http://arxiv.org/abs/2301.11233

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Evaluation tracks of BiBench. O…

"Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models. (arXiv:2301.11189v1 [eess.IV])" — A non-binary discriminator that is conditioned on quantized local image representations obtained via VQ-VAE autoencoders, for lossy image compression.

Paper: http://arxiv.org/abs/2301.11189

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Comparison of distortion vs. st…

"Revisiting Temporal Modeling for CLIP-based Image-to-Video Knowledge Transferring. (arXiv:2301.11116v1 [cs.CV])" — A look at temporal modeling in the context of image-to-video knowledge transferring, which is the key point for extending image-text pretrained models to the video domain.

Paper: http://arxiv.org/abs/2301.11116

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(a) Illustration of temporal mo…

"Explaining Visual Biases as Words by Generating Captions. (arXiv:2301.11104v1 [cs.LG])" — Diagnosing the potential biases in image classifiers by leveraging two types (generative and discriminative) of pre-trained vision-language models to describe the visual bias as a word.

Paper: http://arxiv.org/abs/2301.11104

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Concept of the proposed bias-to…

"Vision-Language Models Performing Zero-Shot Tasks Exhibit Gender-based Disparities. (arXiv:2301.11100v1 [cs.CV])" — An exploration of the extent to which zero-shot vision-language models exhibit gender bias for different vision tasks.

Paper: http://arxiv.org/abs/2301.11100

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(a) The average precision (AP) …

"simple diffusion: End-to-end diffusion for high resolution images. (arXiv:2301.11093v1 [cs.CV])" — Improve denoising diffusion for high resolution images while keeping the model as simple as possible and obtaining performance comparable to the latent diffusion-based approaches?

Paper: http://arxiv.org/abs/2301.11093

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A dslr photo of a frog wearing…

"Rewarded meta-pruning: Meta Learning with Rewards for Channel Pruning. (arXiv:2301.11063v1 [cs.CV])" — A method to reduce the parameters and FLOPs for computational efficiency in deep learning models by introducing accuracy and efficiency coefficients to control the trade-off between the accuracy of the network and its computing efficiency.

Paper: http://arxiv.org/abs/2301.11063

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Reward at varying Accuracies an…

"Explore the Power of Dropout on Few-shot Learning. (arXiv:2301.11015v1 [cs.CV])" — An exploration of the power of the dropout regularization technique on few-shot learning and provide some insights about how to use it.

Paper: http://arxiv.org/abs/2301.11015

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The generalization power of tra…

"On the Importance of Noise Scheduling for Diffusion Models. (arXiv:2301.10972v1 [cs.CV])" — A study of the effect of noise scheduling strategies for denoising diffusion generative models which finds that the noise scheduling is crucial for performance.

Paper: http://arxiv.org/abs/2301.10972

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Random samples generated by our…

"ITstyler: Image-optimized Text-based Style Transfer. (arXiv:2301.10916v1 [cs.CV])" — A data-efficient text-based style transfer method that does not require optimization at the inference stage where the text input is converted to the style space of the pre-trained VGG network to realize a more effective style swap.

Paper: http://arxiv.org/abs/2301.10916

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Overview stylization results of…

"Distilling Cognitive Backdoor Patterns within an Image. (arXiv:2301.10908v1 [cs.LG])" — A simple method to distill and detect backdoor patterns within an image by extracting the "minimal essence" from an input image responsible for the model's prediction.

Paper: http://arxiv.org/abs/2301.10908
Code: https://github.com/HanxunH/CognitiveDistillation

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On the left, First row: a clean…

"Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. (arXiv:2108.13161v7 [cs.CL] CROSS LISTED)" — A novel pluggable, extensible, and efficient large-scale pre-trained language model approach which can convert small language models into better few-shot learners without any prompt engineering.

Paper: http://arxiv.org/abs/2108.13161
Code: https://github.com/zjunlp/DART

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The architecture of DifferentiA…

"VN-Transformer: Rotation-Equivariant Attention for Vector Neurons. (arXiv:2206.04176v3 [cs.CV] UPDATED)" — A novel "VN-Transformer" architecture to address several shortcomings of the current Vector Neuron (VN) models.

Paper: http://arxiv.org/abs/2206.04176

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VN-Transformer (“early fusion”)…