Search Results for author:
Found 29 papers, 15 papers with code
CoSurfGS:Collaborative 3D Surface Gaussian Splatting with Distributed Learning for Large Scene Reconstruction
3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction.
LLaVA-SLT: Visual Language Tuning for Sign Language Translation
We propose hierarchical visual encoder that learns a robust word-level intermediate representation that is compatible with LLM token embeddings.
Splatter-360: Generalizable 360$^{\circ}$ Gaussian Splatting for Wide-baseline Panoramic Images
Wide-baseline panoramic images are frequently used in applications like VR and simulations to minimize capturing labor costs and storage needs.
Unleashing the Potential of Multi-modal Foundation Models and Video Diffusion for 4D Dynamic Physical Scene Simulation
Realistic simulation of dynamic scenes requires accurately capturing diverse material properties and modeling complex object interactions grounded in physical principles.
DATAP-SfM: Dynamic-Aware Tracking Any Point for Robust Structure from Motion in the Wild
To tackle these challenges, we propose a dynamic-aware tracking any point (DATAP) method that leverages consistent video depth and point tracking.
DGTR: Distributed Gaussian Turbo-Reconstruction for Sparse-View Vast Scenes
This paper presents DGTR, a novel distributed framework for efficient Gaussian reconstruction for sparse-view vast scenes.
DiffPano: Scalable and Consistent Text to Panorama Generation with Spherical Epipolar-Aware Diffusion
Then, we propose a novel text-driven panoramic generation framework, termed DiffPano, to achieve scalable, consistent, and diverse panoramic scene generation.
Where Am I and What Will I See: An Auto-Regressive Model for Spatial Localization and View Prediction
Our model simultaneously estimates the camera pose from a single image and predicts the view from a new camera pose, effectively bridging the gap between spatial awareness and visual prediction.
HiSplat: Hierarchical 3D Gaussian Splatting for Generalizable Sparse-View Reconstruction
Recently, advances in generalizable 3D Gaussian Splatting have enabled high-quality novel view synthesis for unseen scenes from sparse input views by feed-forward predicting per-pixel Gaussian parameters without extra optimization.
StreetSurfGS: Scalable Urban Street Surface Reconstruction with Planar-based Gaussian Splatting
Reconstructing urban street scenes is crucial due to its vital role in applications such as autonomous driving and urban planning.
GigaGS: Scaling up Planar-Based 3D Gaussians for Large Scene Surface Reconstruction
To this end, we propose GigaGS, the first work for high-quality surface reconstruction for large-scale scenes using 3DGS.
DynaSurfGS: Dynamic Surface Reconstruction with Planar-based Gaussian Splatting
Extensive experiments demonstrate that DynaSurfGS surpasses state-of-the-art methods in both high-fidelity surface reconstruction and photorealistic rendering.
ND-SDF: Learning Normal Deflection Fields for High-Fidelity Indoor Reconstruction
Neural implicit reconstruction via volume rendering has demonstrated its effectiveness in recovering dense 3D surfaces.
NeuRodin: A Two-stage Framework for High-Fidelity Neural Surface Reconstruction
Signed Distance Function (SDF)-based volume rendering has demonstrated significant capabilities in surface reconstruction.
VIPeR: Visual Incremental Place Recognition with Adaptive Mining and Continual Learning
Then, to prevent catastrophic forgetting in lifelong learning, we draw inspiration from human memory systems and design a novel memory bank for our VIPeR.
MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers
Recently, 3D assets created via reconstruction and generation have matched the quality of manually crafted assets, highlighting their potential for replacement.
PGSR: Planar-based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstruction
Experiments on indoor and outdoor scenes show that our method achieves fast training and rendering while maintaining high-fidelity rendering and geometric reconstruction, outperforming 3DGS-based and NeRF-based methods.
Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers
Sora unveils the potential of scaling Diffusion Transformer for generating photorealistic images and videos at arbitrary resolutions, aspect ratios, and durations, yet it still lacks sufficient implementation details.
Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy
In this paper, we propose a novel SSM-based point cloud processing backbone, named Point Mamba, with a causality-aware ordering mechanism.
NeRF-Det++: Incorporating Semantic Cues and Perspective-aware Depth Supervision for Indoor Multi-View 3D Detection
We project the freely available 3D segmentation annotations onto the 2D plane and leverage the corresponding 2D semantic maps as the supervision signal, significantly enhancing the semantic awareness of multi-view detectors.
Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning
These outcomes suggest that the 3D point cloud is a valuable observation modality for intricate robotic tasks.
DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Iterative Diffusion-Based Refinement
Furthermore we also develop an uncertainty estimation module within diffusion to evaluate the reliability of estimated scene flow.
DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Diffusion Model
Furthermore, we also develop an uncertainty estimation module within diffusion to evaluate the reliability of estimated scene flow.
Improving Feature-based Visual Localization by Geometry-Aided Matching
We apply GAM to a new hierarchical visual localization pipeline and show that GAM can effectively improve the robustness and accuracy of localization.
IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View Synthesis
Existing inverse rendering combined with neural rendering methods can only perform editable novel view synthesis on object-specific scenes, while we present intrinsic neural radiance fields, dubbed IntrinsicNeRF, which introduce intrinsic decomposition into the NeRF-based neural rendering method and can extend its application to room-scale scenes.
iDF-SLAM: End-to-End RGB-D SLAM with Neural Implicit Mapping and Deep Feature Tracking
The neural implicit mapper is trained on-the-fly, while though the neural tracker is pretrained on the ScanNet dataset, it is also finetuned along with the training of the neural implicit mapper.
D$^3$FlowSLAM: Self-Supervised Dynamic SLAM with Flow Motion Decomposition and DINO Guidance
We propose a dynamic update module based on this representation and develop a dense SLAM system that excels in dynamic scenarios.
PVO: Panoptic Visual Odometry
We present PVO, a novel panoptic visual odometry framework to achieve more comprehensive modeling of the scene motion, geometry, and panoptic segmentation information.
Hybrid Tracker with Pixel and Instance for Video Panoptic Segmentation
HybridTracker performs pixel tracker and instance tracker in parallel to obtain the association matrices, which are fused into a matching matrix.
