https://github.com/prgumd/0-MMS
공식 코드0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/princeton-nlp/mquake
공식 코드MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
https://github.com/princetonvisualai/merv
공식 코드Unifying Specialized Visual Encoders for Video Language Models
https://github.com/princetonvisualai/mqvr
공식 코드https://github.com/pris-cv/cinetechbench
공식 코드CineTechBench: A Benchmark for Cinematographic Technique Understanding and Generation
https://github.com/pritamqu/XKD
공식 코드XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning
https://github.com/pritamqu/vcrbench
공식 코드VCRBench: Exploring Long-form Causal Reasoning Capabilities of Large Video Language Models
https://github.com/privateyoung/Youtube-NT
공식 코드Hierarchical Autoregressive Modeling for Neural Video Compression
https://github.com/proteus1991/RawVSR
공식 코드Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference
https://github.com/proteus1991/pscc-net
공식 코드https://github.com/prototypenx/efficientmt
공식 코드EfficientMT: Efficient Temporal Adaptation for Motion Transfer in Text-to-Video Diffusion Models
https://github.com/prouast/ctc-intake-detection
공식 코드Single-stage intake gesture detection using CTC loss and extended prefix beam search
https://github.com/prouast/deep-intake-detection
공식 코드Learning deep representations for video-based intake gesture detection
https://github.com/psaltaath/tadn-mot
공식 코드Transformer-based assignment decision network for multiple object tracking
https://github.com/psh01087/Vid-ODE
공식 코드Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation
https://github.com/pshams55/AMIL
공식 코드AMIL: Adversarial Multi Instance Learning for Human Pose Estimation
https://github.com/psmmettes/object-priors-unseen-actions
공식 코드https://github.com/ptirupat/MLAD
공식 코드Modeling Multi-Label Action Dependencies for Temporal Action Localization
https://github.com/ptoupas/harflow3d
공식 코드HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices
https://github.com/purduedigitaltwin/seneva
공식 코드Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
https://github.com/putshua/inference-scale-ann-snn
공식 코드Inference-Scale Complexity in ANN-SNN Conversion for High-Performance and Low-Power Applications
https://github.com/pxiangwu/MotionNet
공식 코드https://github.com/py85252876/mmvgm
공식 코드https://github.com/py85252876/uvd
공식 코드https://github.com/pykale/pykale
공식 코드PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python
https://github.com/pytorch/fairseq
공식 코드VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding
https://github.com/q-future/q-align
공식 코드Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels
https://github.com/q-future/visual-question-answering-for-video-quality-assessment
공식 코드VQA$^2$: Visual Question Answering for Video Quality Assessment
https://github.com/qa276390/searchtrack
공식 코드SearchTrack: Multiple Object Tracking with Object-Customized Search and Motion-Aware Features
https://github.com/qduOliver/MQP
공식 코드A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality Perception
https://github.com/qilimk/biggan-am
공식 코드https://github.com/qingchen239/ld-detr
공식 코드LD-DETR: Loop Decoder DEtection TRansformer for Video Moment Retrieval and Highlight Detection
https://github.com/qinghua-zhou/stealth-edits
공식 코드https://github.com/qinying-liu/c3bn
공식 코드Convex Combination Consistency between Neighbors for Weakly-supervised Action Localization
https://github.com/qinying-liu/case
공식 코드https://github.com/qiujihao19/artemis
공식 코드Artemis: Towards Referential Understanding in Complex Videos
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.