https://github.com/farewellthree/BT-Adapter
공식 코드BT-Adapter: Video Conversation is Feasible Without Video Instruction Tuning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/farewellthree/ppllava
공식 코드PPLLaVA: Varied Video Sequence Understanding With Prompt Guidance
https://github.com/farewellthree/stan
공식 코드Revisiting Temporal Modeling for CLIP-based Image-to-Video Knowledge Transferring
https://github.com/fast-vid2vid/fast-vid2vid
공식 코드Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis
https://github.com/fatemehazimi990/HS2S
공식 코드Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching
https://github.com/fatemehazimi990/RS2S
공식 코드Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory
https://github.com/fau-is/next-best-action
공식 코드Prescriptive Business Process Monitoring for Recommending Next Best Actions
https://github.com/fau-is/xnap
공식 코드XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP
https://github.com/fau-lms/bjontegaard
공식 코드The Bjøntegaard Bible -- Why your Way of Comparing Video Codecs May Be Wrong
https://github.com/fau-lms/vvc-extension-ged
공식 코드https://github.com/fbarez/neuroplasticity
공식 코드https://github.com/fcakir/mihash
공식 코드https://github.com/fcntes/indoordepth
공식 코드Deeper into Self-Supervised Monocular Indoor Depth Estimation
https://github.com/fcongrui/3dattgan
공식 코드https://github.com/feichtenhofer/st-resnet
공식 코드Spatiotemporal Residual Networks for Video Action Recognition
https://github.com/feichtenhofer/twostreamfusion
공식 코드Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/feinanshan/m2m_vfi
공식 코드Many-to-many Splatting for Efficient Video Frame Interpolation
https://github.com/feipengma6/vsc22-submission
공식 코드https://github.com/feizc/video-in-context
공식 코드https://github.com/felixfeng2019/struggle-determination
공식 코드Are you Struggling? Dataset and Baselines for Struggle Determination in Assembly Videos
https://github.com/fengzicai/awesomewmad
공식 코드https://github.com/fengzicai/wmad-benchmarks
공식 코드https://github.com/fepegar/gestures-miccai-2021
공식 코드Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures
https://github.com/feyzaakyurek/dune
공식 코드https://github.com/ffmpbgrnn/yt8m
공식 코드https://github.com/fidsinn/sporttaskme22
공식 코드Fine-Grained Action Detection with RGB and Pose Information using Two Stream Convolutional Networks
https://github.com/final-0/sa-icm
공식 코드Image Coding for Machines with Edge Information Learning Using Segment Anything
https://github.com/firework8/brl
공식 코드Balanced Representation Learning for Long-tailed Skeleton-based Action Recognition
https://github.com/fisseha21/z-upscaling
공식 코드Z-upscaling: Optical Flow Guided Frame Interpolation for Isotropic Reconstruction of 3D EM Volumes
https://github.com/fjchange/MIST_VAD
공식 코드MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection
https://github.com/fjchange/him-net
공식 코드Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning
https://github.com/flageval-baai/flagevalmm
공식 코드FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation
https://github.com/flamewei123/DEPN
공식 코드DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models
https://github.com/fletcherjiang/llmepet
공식 코드Prior Knowledge Integration via LLM Encoding and Pseudo Event Regulation for Video Moment Retrieval
https://github.com/flowerfan/trackron
공식 코드https://github.com/fmp453/rectable
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.