arXiv Computer Vision
LighTROcc: Lightweight 4D Occupancy Forecasting via Instance-Centric 3D Gaussians
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arXiv Computer Vision
Sep 3
OccAnyScene: Towards Unified Indoor-Outdoor 3D Occupancy Prediction
OccAnyScene introduces a unified approach for 3D occupancy prediction across both indoor and outdoor scenes, addressing the challenge of handling diverse camera setups, spatial ranges, voxel specifications, and semantic taxonomies. The method builds on a pretrained depth model, using pixel-aligned frustum feature aggregation and frustum-parameterized Gaussian construction to generate scene-adaptive occupancy predictions. It achieves state-of-the-art performance, scoring 59.92% mIoU on Occ-ScanNet and 23.06% mIoU on SurroundOcc-nuScenes.
arXiv Computer Vision
Sep 23
VEOcc: Voxel-Centric Online Semantic Occupancy Prediction For Embodied Scene Understanding
arXiv:2605.25059v4 Announce Type: replace Abstract: Crucial for autonomous exploration, online 3D occupancy prediction and mapping incrementally construct dense spatial representations on the fly. Em...
Hugging Face Trending Papers
Jul 27
InterOCF: Spatio-Temporal 2D-3D Interaction for Camera-Only 4D Occupancy Forecasting
Camera-only 4D occupancy forecasting enables autonomous vehicles to predict future 3D semantic scenes solely from historical multi-view images, which is critical for driving safety. Even though current methods have achieved good performance, the strong spatial-temporal modeling between the input multi-view frames is still underexplored, which limits the performance of those methods in future 4D forecasting.
arXiv Computer Vision
Aug 26
O3N: Omnidirectional Open-Vocabulary Occupancy Prediction for Embodied Intelligent Robotics
O3N is a novel framework that performs open‑vocabulary occupancy prediction from a single omnidirectional RGB image. It introduces a polar‑spiral voxel embedding (PsM) for continuous 360° spatial representation, an Occupancy Cost Aggregation (OCA) module that unifies geometric and semantic supervision, and a Natural Modality Alignment (NMA) pathway that aligns visual, voxel, and text features. Experiments show state‑of‑the‑art results on QuadOcc and Human360Occ benchmarks, with strong cross‑scene generalization and semantic scalability.
arXiv Computer Vision
Sep 23
Leveraging Vision-Based Point Cloud Map Priors for Camera-Based 3D Object Detection and Online Vectorized HD Mapping
The paper presents a framework that builds a static point cloud prior map from past camera traversals, augmenting each point with DINOv3 semantic features. During runtime, a local prior patch is retrieved, encoded with a sparse voxel backbone, and fused with lifted multi‑view camera features in bird’s‑eye view. This fused representation is then used by sparse transformer heads to predict 3D objects and vectorized map elements, achieving improved performance on Argoverse 2 without requiring LiDAR for prior‑map construction or online inference.
arXiv AI
Jun 19
Class-Incremental Motion Forecasting
arXiv:2603. 09420v3 Announce Type: replace-cross Abstract: Motion forecasting enables autonomous vehicles to anticipate scene evolution by predicting the future trajectories of dynamic agents.