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

https://github.com/aaronbtb/mnerv

공식 코드

MNeRV: A Multilayer Neural Representation for Videos

https://github.com/aaronkandel/wasserstein-nonlinear-mpc

공식 코드

Safe Learning MPC with Limited Model Knowledge and Data

https://github.com/aashgan/temporalperturbsum

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Does SpatioTemporal information benefit Two video summarization benchmarks?

https://github.com/abcyzj/Semantics2Hands

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Semantics2Hands: Transferring Hand Motion Semantics between Avatars

https://github.com/abcyzj/meshret

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Skinned Motion Retargeting with Dense Geometric Interaction Perception

https://github.com/abduallahmohamed/FollowMe

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FollowMe: Vehicle Behaviour Prediction in Autonomous Vehicle Settings

https://github.com/abduallahmohamed/Social-STGCNN

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Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction

https://github.com/abduallahmohamed/skeleton-graph

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Skeleton-Graph: Long-Term 3D Motion Prediction From 2D Observations Using Deep Spatio-Temporal Graph CNNs

https://github.com/abduallahmohamed/social-implicit

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Social-Implicit: Rethinking Trajectory Prediction Evaluation and The Effectiveness of Implicit Maximum Likelihood Estimation

https://github.com/abewley/sort

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Simple Online and Realtime Tracking

https://github.com/abhijay9/shifttolerant-lpips

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Shift-tolerant Perceptual Similarity Metric

https://github.com/abhinanda-punnakkal/BABEL

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BABEL: Bodies, Action and Behavior with English Labels

https://github.com/abhyantrika/nirvana

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NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling

https://github.com/aboah1994/deepsegment

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DeepSegmenter: Temporal Action Localization for Detecting Anomalies in Untrimmed Naturalistic Driving Videos

https://github.com/aboulch/tec_prediction

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Ionospheric activity prediction using convolutional recurrent neural networks

https://github.com/acerkoo/disco

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Outdated Issue Aware Decoding for Reasoning Questions on Edited Knowledge

https://github.com/adap/flower

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Federated Self-supervised Learning for Video Understanding

https://github.com/adaptivetokensampling/ATS

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Adaptive Token Sampling For Efficient Vision Transformers

https://github.com/adeboissiere/FUSION-human-action-recognition

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Infrared and 3D skeleton feature fusion for RGB-D action recognition

https://github.com/adityac94/Grad_CAM_plus_plus

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Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks

https://github.com/adityavavre/videgovlm

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EgoVLM: Policy Optimization for Egocentric Video Understanding

https://github.com/adnanb97/opencv-multiple-object-tracking

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Multiple Object Trackers in OpenCV: A Benchmark

https://github.com/adnortje/deepvideo

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Deep motion estimation for parallel inter-frame prediction in video compression

https://github.com/adrianofragomeni/contra

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ConTra: (Con)text (Tra)nsformer for Cross-Modal Video Retrieval

https://github.com/adxcreative/EERCF

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Towards Efficient and Effective Text-to-Video Retrieval with Coarse-to-Fine Visual Representation Learning

https://github.com/aengusl/latent-adversarial-training

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Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs

https://github.com/afperezm/acoustic-images-distillation

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Audio-Visual Model Distillation Using Acoustic Images

https://github.com/againerju/tcg_recognition

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Traffic Control Gesture Recognition for Autonomous Vehicles

https://github.com/agao8/STEAD

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STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive Applications

https://github.com/aghdamamir/actalign

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ActAlign: Zero-Shot Fine-Grained Video Classification via Language-Guided Sequence Alignment

https://github.com/ahmad-573/vurf

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VURF: A General-purpose Reasoning and Self-refinement Framework for Video Understanding

https://github.com/ahmed-nady/multimodal-action-recognition

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EPAM-Net: An Efficient Pose-driven Attention-guided Multimodal Network for Video Action Recognition

https://github.com/ahmetakman/e-vfia

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E-VFIA : Event-Based Video Frame Interpolation with Attention

https://github.com/ahmetakman/maevi

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MAEVI: Motion Aware Event-Based Video Frame Interpolation

https://github.com/ahupujr/refid

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A Unified Framework for Event-based Frame Interpolation with Ad-hoc Deblurring in the Wild

https://github.com/ai-forever/kandinsky-3

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Kandinsky 3.0 Technical Report

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