**Efficient4D: Fast Dynamic 3D Object Generation from a Single-view Video** The paper presents Efficient4D, a novel framework for generating dynamic 4D objects from a single-view video. The main challenge in this task is the lack of 4D-labeled data, which makes it difficult to train models that can generate high-quality, consistent 4D content. Efficient4D addresses this by using a two-stage approach: first, generating high-quality, spacetime-consistent images under different camera views, and then using these images as labeled data to reconstruct the 4D content through a 4D Gaussian splatting model. This method achieves real-time rendering under continuous camera trajectories and robust reconstruction under sparse views through an inconsistency-aware confidence-weighted loss design and a lightly weighted score distillation loss. **Key Contributions:** 1. **Efficiency:** Efficient4D significantly reduces the training time compared to previous methods, achieving a 10-fold increase in speed while maintaining high-quality novel view synthesis. 2. **Robustness:** The method can handle sparse views and few-shot settings, making it more practical and versatile. 3. **Innovation:** The use of 4D Gaussian splatting and the design of an inconsistency-aware loss function enable efficient and robust 4D reconstruction. **Methods:** - **Image Synthesis:** The first stage involves generating consistent multi-view videos using a modified version of SyncDreamer, which ensures both spatial and temporal consistency. - **4D Reconstruction:** The second stage uses the generated images to train a 4D Gaussian splatting model, which can efficiently and robustly reconstruct dynamic 4D content. **Experiments:** - **Synthetic Data:** Efficient4D outperforms state-of-the-art methods in terms of image quality and temporal smoothness, as measured by metrics like CLIP and LPIPS scores. - **Real Data:** The method is evaluated on both synthetic and real videos, showing superior results in generating high-quality 4D content. - **Sparse Input:** The method effectively handles extremely sparse input scenarios, generating smooth dynamics with only two input frames. **Conclusion:** Efficient4D provides a fast and efficient solution for generating dynamic 4D objects from a single-view video, achieving significant speed improvements and maintaining high-quality reconstruction. The method's robustness and versatility make it a promising approach for various applications in 4D content generation.**Efficient4D: Fast Dynamic 3D Object Generation from a Single-view Video** The paper presents Efficient4D, a novel framework for generating dynamic 4D objects from a single-view video. The main challenge in this task is the lack of 4D-labeled data, which makes it difficult to train models that can generate high-quality, consistent 4D content. Efficient4D addresses this by using a two-stage approach: first, generating high-quality, spacetime-consistent images under different camera views, and then using these images as labeled data to reconstruct the 4D content through a 4D Gaussian splatting model. This method achieves real-time rendering under continuous camera trajectories and robust reconstruction under sparse views through an inconsistency-aware confidence-weighted loss design and a lightly weighted score distillation loss. **Key Contributions:** 1. **Efficiency:** Efficient4D significantly reduces the training time compared to previous methods, achieving a 10-fold increase in speed while maintaining high-quality novel view synthesis. 2. **Robustness:** The method can handle sparse views and few-shot settings, making it more practical and versatile. 3. **Innovation:** The use of 4D Gaussian splatting and the design of an inconsistency-aware loss function enable efficient and robust 4D reconstruction. **Methods:** - **Image Synthesis:** The first stage involves generating consistent multi-view videos using a modified version of SyncDreamer, which ensures both spatial and temporal consistency. - **4D Reconstruction:** The second stage uses the generated images to train a 4D Gaussian splatting model, which can efficiently and robustly reconstruct dynamic 4D content. **Experiments:** - **Synthetic Data:** Efficient4D outperforms state-of-the-art methods in terms of image quality and temporal smoothness, as measured by metrics like CLIP and LPIPS scores. - **Real Data:** The method is evaluated on both synthetic and real videos, showing superior results in generating high-quality 4D content. - **Sparse Input:** The method effectively handles extremely sparse input scenarios, generating smooth dynamics with only two input frames. **Conclusion:** Efficient4D provides a fast and efficient solution for generating dynamic 4D objects from a single-view video, achieving significant speed improvements and maintaining high-quality reconstruction. The method's robustness and versatility make it a promising approach for various applications in 4D content generation.