Déjà View applies a single looped transformer block recurrently to per-view features for K refinement steps, making explicit the iterative refinement that multi-view reconstruction transformers otherwise buy inefficiently through unique parameters …
Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-observed regions. ArtiFixer bridges 3D neural reconstruction and auto-regressive video generation to …
MapAnything is a unified transformer-based feed-forward model that ingests one or more images along with optional geometric inputs such as camera intrinsics, poses, depth, or partial reconstructions, and directly regresses metric 3D scene geometry …
We present FlowR, a novel pipeline that bridges the gap between sparse and dense 3D reconstruction. Contrary to prior works, we learn a direct mapping between incorrect renderings and their corresponding ground-truth images, augmenting scene captures with consistent novel, generated views to improve reconstruction quality.
Given a set of *heterogeneous* input sequences of a common geographic area, we optimize a *single* dynamic scene representation that permits rendering of arbitrary viewpoints and scene configurations at interactive speeds.
We present the *first benchmark* and a *novel method* for radiance field reconstruction of dynamic urban areas from *heterogeneous, multi-sequence data*.
We present R3D3, a method for dense 3D reconstruction and ego-motion estimation in dynamic outdoor environments that iterates between geometric multi-camera optimization and monocular depth refinement.
A reliable and accurate 3D tracking framework is essential for predicting future locations of surrounding objects and planning the observer's actions in numerous applications such as autonomous driving. We propose a framework that can effectively …
Object tracking and 3D reconstruction are often performed together, with tracking used as input for reconstruction. However, the obtained reconstructions also provide useful information for improving tracking. We propose a novel method that closes …