Geo-Align applies RL with a perceptual reward derived from 3D camera trajectory estimation to improve controllability and fidelity in video generation without paired training data.
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Grounding image matching in 3d with mast3r
26 Pith papers cite this work. Polarity classification is still indexing.
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representative citing papers
GenRecon lifts object-level generative priors to scene-scale reconstruction by chunking scenes and using projection-based conditioning on multi-view features, claiming 16% better results than prior methods.
NoPo4D is the first feed-forward system for dynamic 4D Gaussian splatting from unposed multi-view videos, using velocity decomposition supervised by optical flow and a bidirectional motion encoder.
CRePE supplies depth-aware positional distributions along curved rays for stable unified-camera control in frozen video DiT models.
WildSplatter jointly learns 3D Gaussians and appearance embeddings from unconstrained photo collections to enable fast feed-forward reconstruction and flexible lighting control in 3D Gaussian Splatting.
A new benchmark with real lunar stereo ground truth and analog data shows that sim-to-real fine-tuned monocular depth models achieve large in-domain gains but minimal generalization to actual lunar images.
Affostruction reconstructs full 3D object geometry from partial RGBD views and grounds text-based affordances on both visible and unobserved surfaces, reporting large gains over prior methods.
FastForward represents scenes as collections of 3D-anchored image features and performs camera pose estimation via feed-forward correspondence prediction, achieving competitive accuracy with minimal mapping time.
Modality Forcing lets a single DiT produce image and depth outputs in any order after training on sparse real-world depth, with larger image-pretrained models yielding better depth accuracy and a 57% AbsRel reduction versus prior joint generative baselines.
Robust Dreamer uses Latent Gaussian Memory anchored to diffusion latents and Deviation Learning with a Dynamic Deviation Archive to reduce drift in long-horizon action-controlled image-to-video generation, reporting SOTA results on ScanNet, DL3DV, and OmniWorldGame.
SADGE is a new fused similarity metric combining DINOv3 appearance and MASt3R geometry via constrained bilinear interaction that correlates with downstream synthetic-to-real performance at Pearson r=0.88 across multiple benchmarks.
SpaceMind++ adds an explicit voxelized allocentric cognitive map and coordinate-guided fusion to video MLLMs, claiming SOTA on VSI-Bench and improved out-of-distribution generalization on three other 3D benchmarks.
FluSplat trains a model with geometric alignment constraints on multi-view edits to produce consistent 3D scene edits from sparse views in a single forward pass without test-time optimization.
Reframing head pose estimation as relative pose prediction between image pairs enables a synthetic-only trained model to outperform absolute regression methods on real benchmarks.
A feed-forward video latent transformer that predicts time-varying 3D Gaussian primitives from one image to produce controllable 4D scenes with appearance, geometry, and motion.
A causal transformer with key-value caching and distillation from a bidirectional VGGT model enables efficient online 4D geometry reconstruction from videos.
RoDyGS separates static and dynamic elements in monocular videos using Gaussian splatting with regularization and introduces the Kubric-MRig benchmark for pose-free dynamic novel view synthesis.
Introduces an eager-mode PyTorch BA library with GPU-accelerated sparse ops claiming 18.5-23x speedups over GTSAM, g2o, and Ceres.
ViewCrafter tames video diffusion models with point-based 3D guidance and iterative trajectory planning to produce high-fidelity novel views from single or sparse images.
VGP-Nav resolves monocular scale ambiguity online via ground-plane geometry to produce metric localization and obstacle maps from RGB alone for robot navigation.
SAVMap extracts semantic structure points from panoramic video, tracks them across rectified views, and recovers 3D wireframe maps via Manhattan-constrained SfM, reporting 4.8 cm aggregate MAE over 5000 shelf elements in a 46-row warehouse.
An adaptive multi-criteria feature selection policy for 3D scene reconstruction that outperforms random, texture-only, and uniform-grid baselines on synthetic multi-view tests for completeness and RMSE.
PatchPoison injects 12x12 pixel checkerboard patches into multi-view images to disrupt SfM feature matching, causing 3DGS reconstructions to diverge with 6.8x higher LPIPS error on NeRF-Synthetic while remaining unobtrusive.
UniDepthV2 predicts metric 3D points directly from single images using a self-promptable camera module, pseudo-spherical representation, and new losses for improved cross-domain generalization.
citing papers explorer
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ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis
ViewCrafter tames video diffusion models with point-based 3D guidance and iterative trajectory planning to produce high-fidelity novel views from single or sparse images.