Syn4D: A Multiview Synthetic 4D Dataset
Dense 3D reconstruction and tracking of dynamic scenes from monocular video remains an important open challenge in computer vision. Progress in this area has been constrained by the scarcity of high-quality datasets with dense, complete, and accurate geometric annotations. To address this limitation, we introduce Syn4D, a multiview synthetic dataset of dynamic scenes that includes ground-truth camera motion, depth maps, dense tracking, and parametric human pose annotations. A key feature of Syn4D is the ability to unproject any pixel into 3D to any time and to any camera. We conduct extensive evaluations across multiple downstream tasks to demonstrate the utility and effectiveness of the proposed dataset, including 4D scene reconstruction, 3D point tracking, geometry-aware camera retargeting, and human pose estimation. The experimental results highlight Syn4D's potential to facilitate research in dynamic scene understanding and spatiotemporal modeling.
Code (0)
등록된 구현이 없습니다.
Tasks
Scene Understanding3D ReconstructionPose EstimationPoint TrackingSimilar Papers 제목 키워드 기반
SiM3D: Single-instance Multiview Multimodal and Multisetup 3D Anomaly Detection Benchmark
We propose SiM3D, the first benchmark considering the integration of multiview and multimodal information for comprehensive 3D anomaly detection and segmentation (ADS), where the task is to produce a voxel-based Anomaly …
3D Anomaly Detection3D Anomaly Detection and SegmentationAnomaly DetectionMultiview Detection with Feature Perspective Transformation
Incorporating multiple camera views for detection alleviates the impact of occlusions in crowded scenes. In a multiview system, we need to answer two important questions when dealing with ambiguities that arise from occl…
Human DetectionMultiview DetectionPedestrian DetectionMVD$^2$: Efficient Multiview 3D Reconstruction for Multiview Diffusion
As a promising 3D generation technique, multiview diffusion (MVD) has received a lot of attention due to its advantages in terms of generalizability, quality, and efficiency. By finetuning pretrained large image diffusio…
3D Generation3D ReconstructionNeRSP: Neural 3D Reconstruction for Reflective Objects with Sparse Polarized Images
We present NeRSP, a Neural 3D reconstruction technique for Reflective surfaces with Sparse Polarized images. Reflective surface reconstruction is extremely challenging as specular reflections are view-dependent and thus …
3D ReconstructionSurface ReconstructionPIEs: Pose Invariant Embeddings
The role of pose invariance in image recognition and retrieval is studied. A taxonomic classification of embeddings, according to their level of invariance, is introduced and used to clarify connections between existing …
General ClassificationRetrieval