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Animation

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/RaphaelBensTAU/animation_masking_w_bg

Image Animation with Perturbed Masks

https://github.com/Sainzerjj/UniAnimate

UniAnimate: Taming Unified Video Diffusion Models for Consistent Human Image Animation

https://github.com/Saritus/Crowd-Counter

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/UCB-ICSI-Vision-Group/decaf-release

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

https://github.com/UCBAIR/decaf-release

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

https://github.com/Wangt-CN/DisCo

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

https://github.com/abhaskumarsinha/KMT

First Order Motion Model for Image Animation

https://github.com/ahmedest61/vlad-buff

Deep Attentional Structured Representation Learning for Visual Recognition

https://github.com/anwesanpal/DEDUCE

DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments

https://github.com/arthur-qiu/FreeNoise-AnimateDiff

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

https://github.com/baldassarreFe/deep-koalarization

CNN Features off-the-shelf: an Astounding Baseline for Recognition

https://github.com/bujiazi/motionclone

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

https://github.com/caihuaiguang/CHG-Shapley-for-Data-Selection

Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision

https://github.com/dattatrayshinde/oc_sd

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/decile-team/cords

Learning From Less Data: A Unified Data Subset Selection and Active Learning Framework for Computer Vision

https://github.com/deepbrainai-research/prioritycut

PriorityCut: Occlusion-guided Regularization for Warp-based Image Animation

https://github.com/fudan-generative-vision/hallo

Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image Animation

https://github.com/goluck-konuko/animation-based-codecs

Ultra-low bitrate video conferencing using deep image animation

https://github.com/haysacks/spot-the-coin

Bilinear CNNs for Fine-grained Visual Recognition

https://github.com/jetpacapp/DeepBeliefSDK

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

https://github.com/jialetao/dam

Move As You Like: Image Animation in E-Commerce Scenario

https://github.com/jimgoo/caffe-oxford102

CNN Features off-the-shelf: an Astounding Baseline for Recognition

https://github.com/joshuaczhao/CNN-Sentence-Classifier-Reproduction

CNN Features off-the-shelf: an Astounding Baseline for Recognition

https://github.com/karanjsingh/Improved-CSRNet

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/krutikabapat/Crowd_Counting

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/laura-wang/video_repres_mas

Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics

https://github.com/leeyeehoo/CSRNet-pytorch

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

https://github.com/levyisthebest/echopulse_prelease

Moonshot: Towards Controllable Video Generation and Editing with Multimodal Conditions

https://github.com/lpengyang/motionclone

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

https://github.com/magic-research/magic-animate

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

https://github.com/mangonihao/BiLinear_CNN

Bilinear CNNs for Fine-grained Visual Recognition

https://github.com/neuroailab/LocalAggregation-Pytorch

Local Aggregation for Unsupervised Learning of Visual Embeddings

https://github.com/numpde/phonepad

Classifying Variable-Length Audio Files with All-Convolutional Networks and Masked Global Pooling

https://github.com/nvidiagameworks/kaolin-wisp

Neural Fields in Visual Computing and Beyond

https://github.com/showlab/diffsim

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

https://github.com/snap-research/panda-70m

AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.