Efficient4D is a fast and efficient framework for generating dynamic 3D objects from a single-view video. The method addresses the challenge of generating high-quality, spacetime-consistent images across different camera views, which are then used as labeled data to reconstruct 4D content using a 4D Gaussian splatting model. Efficient4D achieves real-time rendering under continuous camera trajectories and introduces an inconsistency-aware confidence-weighted loss design along with a lightly weighted score distillation loss to enable robust reconstruction under sparse views. The method significantly improves speed compared to prior art, achieving a 10-fold increase in speed while maintaining the quality of novel view synthesis. For example, Efficient4D takes only 10 minutes to model a dynamic object, compared to 120 minutes by the previous art model Consistent4D. The method is publicly available at https://github.com/fudan-zvg/Efficient4D. The framework consists of two stages: first, generating consistent multi-view videos with spatial and temporal coherence, and second, rapidly producing 4D object reconstructions. The method utilizes image supervision with lightly weighted SDS loss, significantly accelerating the generation process and achieving about 10 times faster speeds compared to previous works while delivering superior reconstruction and novel view synthesis results. Additionally, the model is effective in extremely sparse input scenarios, requiring only two available images, thereby expanding its application scope.Efficient4D is a fast and efficient framework for generating dynamic 3D objects from a single-view video. The method addresses the challenge of generating high-quality, spacetime-consistent images across different camera views, which are then used as labeled data to reconstruct 4D content using a 4D Gaussian splatting model. Efficient4D achieves real-time rendering under continuous camera trajectories and introduces an inconsistency-aware confidence-weighted loss design along with a lightly weighted score distillation loss to enable robust reconstruction under sparse views. The method significantly improves speed compared to prior art, achieving a 10-fold increase in speed while maintaining the quality of novel view synthesis. For example, Efficient4D takes only 10 minutes to model a dynamic object, compared to 120 minutes by the previous art model Consistent4D. The method is publicly available at https://github.com/fudan-zvg/Efficient4D. The framework consists of two stages: first, generating consistent multi-view videos with spatial and temporal coherence, and second, rapidly producing 4D object reconstructions. The method utilizes image supervision with lightly weighted SDS loss, significantly accelerating the generation process and achieving about 10 times faster speeds compared to previous works while delivering superior reconstruction and novel view synthesis results. Additionally, the model is effective in extremely sparse input scenarios, requiring only two available images, thereby expanding its application scope.