Video Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 19
- 보존된 평가 기록
- 125
Script for Amee Marketing & Trading Company Short Video
(Duration: 45-60 seconds)
Opening Scene (0:00-0:05):
- Visual: Close-up of fresh organic grains spilling gently into a wooden bowl. Sunlight filters through lush green fields.
- Text Overlay: "Nourishing Lives, Naturally."
- Music: Uplifting acoustic melody with a traditional touch.
Scene 1: Organic & Natural Offerings (0:05-0:15):
- Visual: Rapid montage of vibrant vegetables, ripe fruits, aromatic spices, Ayurvedic herbs, and fresh dairy products.
- Voiceover: "At Amee Marketing & Trading, we bring you the purest Vedic organic foods—grains, spices, herbs, and dairy—straight from nature’s bounty."
Scene 2: Engineering & Innovation (0:15-0:25):
- Visual: Split-screen transition:
- Left: Engineers working on agriculture machinery and water treatment systems.
- Right: Automation controls, aquaculture systems, and textile equipment in action.
- Voiceover: "Pioneering sustainable solutions—agriculture engineering, water and wastewater treatment, automation, and industrial innovations."
Scene 3: Waste & Resource Management (0:25-0:35):
- Visual: Waste management systems transforming waste into resources, followed by Roadtech equipment paving roads.
- Text Overlay: "Building a greener future."
- Voiceover: "From waste management to infrastructure, we engineer tomorrow’s world today."
Scene 4: Services & Global Reach (0:35-0:45):
- Visual: Factory assembly line, team meeting, and global map with location pins.
- Voiceover: "As manufacturers, traders, and suppliers, we bridge quality and trust worldwide."
Closing Scene (0:45-0:55):
- Visual: Amee logo fades in over a backdrop of their factory. Contact details appear.
- Text Overlay: "Connect with Us!"
- Phone: +91-8300874712
- Website: www.ameemarketingtredingcompany.in
- Location: Home & Factory (add brief map graphic).
- Voiceover: "Your partner in purity and progress. Contact Amee today!"
End Frame (0:55-1:00):
- Visual: Sunrise over fields with the tagline: "Amee Marketing & Trading – Where Tradition Meets Technology."
Production Notes:
- Music: Blend traditional Indian instruments with modern beats for cross-sector appeal.
- Color Palette: Earthy tones (greens, browns) for organic segments; metallic blues/greys for tech sections.
- Pacing: Quick cuts for energy, but hold 2-3 seconds on contact details.
Perfect for social media ads or website headers! 🌱🚀
Gif credit: MAGVIT
Source: Photo-Realistic Video Prediction on Natural Videos of Largely Changing Frames
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/blackPython/mipae
공식 코드Mutual Information Based Method for Unsupervised Disentanglement of Video Representation
https://github.com/bryanyzhu/Hidden-Two-Stream
공식 코드Exploring Temporal Information for Improved Video Understanding
https://github.com/cagatayyildiz/ODE2VAE
공식 코드ODE$^2$VAE: Deep generative second order ODEs with Bayesian neural networks
https://github.com/chengtan9907/OpenSTL
공식 코드Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning
https://github.com/chengtan9907/simvpv2
공식 코드SimVPv2: Towards Simple yet Powerful Spatiotemporal Predictive Learning
https://github.com/chengyui/sumformer
공식 코드Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach
https://github.com/combi2k2/mg-turbulent-flow
공식 코드https://github.com/czh-98/CMS-LSTM
공식 코드CMS-LSTM: Context Embedding and Multi-Scale Spatiotemporal Expression LSTM for Predictive Learning
https://github.com/dangeng/CorrWiseLosses
공식 코드Comparing Correspondences: Video Prediction with Correspondence-wise Losses
https://github.com/deepextremes/txyxai
공식 코드https://github.com/dun-research/3D-CSL
공식 코드3D-CSL: self-supervised 3D context similarity learning for Near-Duplicate Video Retrieval
https://github.com/earthnet2021/earthnet-model-intercomparison-suite
공식 코드https://github.com/earthnet2021/earthnet-models-pytorch
공식 코드Learning to forecast vegetation greenness at fine resolution over Africa with ConvLSTMs
https://github.com/easylearningscores/pastnet
공식 코드PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction
https://github.com/edenton/svg
공식 코드https://github.com/edouardelasalles/srvp
공식 코드https://github.com/endo-yuki-t/Animating-Landscape
공식 코드https://github.com/exisas/lgc-vd
공식 코드https://github.com/facebookresearch/jepa-intuitive-physics
공식 코드Intuitive physics understanding emerges from self-supervised pretraining on natural videos
https://github.com/foundationvision/omnitokenizer
공식 코드OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation
https://github.com/gaozhangyang/simvp-simpler-yet-better-video-prediction
공식 코드https://github.com/google-research/fitvid
공식 코드https://github.com/google-research/google-research
공식 코드Unsupervised Learning of Object Structure and Dynamics from Videos
https://github.com/google-research/magvit
공식 코드https://github.com/google-research/pix2seq
공식 코드https://github.com/google-research/torchsde
공식 코드https://github.com/holmdk/CloudCast
공식 코드CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds
https://github.com/imanlab/action_conditioned_tactile_prediction
공식 코드Action Conditioned Tactile Prediction: case study on slip prediction
https://github.com/iva-mzsun/moso
공식 코드MOSO: Decomposing MOtion, Scene and Object for Video Prediction
https://github.com/jc043/cpl
공식 코드https://github.com/jcoreyes/OP3
공식 코드Entity Abstraction in Visual Model-Based Reinforcement Learning
https://github.com/jindongjiang/slotssms
공식 코드https://github.com/jthsieh/DDPAE-video-prediction
공식 코드Learning to Decompose and Disentangle Representations for Video Prediction
https://github.com/kaanakan/slamp
공식 코드https://github.com/kay1794/mmvp-motion-matrix-based-video-prediction
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.