8 citations · 33 across the 29 of their papers we have counts for
9 papers · 1 filter
NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes
Muhammad Zubair Irshad, Sergey Zakharov, Katherine Liu +5
Recent implicit neural representations have shown great results for novel view synthesis. However, existing methods require expensive per-scene optimization from many views hence l…
Robust Self-Supervised Extrinsic Self-Calibration
Takayuki Kanai, Igor Vasiljevic, Vitor Guizilini +2
Autonomous vehicles and robots need to operate over a wide variety of scenarios in order to complete tasks efficiently and safely. Multi-camera self-supervised monocular depth esti…
Towards Zero-Shot Scale-Aware Monocular Depth Estimation
Vitor Guizilini, Igor Vasiljevic, Dian Chen +2
Monocular depth estimation is scale-ambiguous, and thus requires scale supervision to produce metric predictions. Even so, the resulting models will be geometry-specific, with lear…
Multi-Object Manipulation via Object-Centric Neural Scattering Functions
Stephen Tian, Yancheng Cai, Hong-Xing Yu +5
Learned visual dynamics models have proven effective for robotic manipulation tasks. Yet, it remains unclear how best to represent scenes involving multi-object interactions. Curre…
HomE: Homography-Equivariant Video Representation Learning
Anirudh Sriram, Adrien Gaidon, Jiajun Wu +3
Recent advances in self-supervised representation learning have enabled more efficient and robust model performance without relying on extensive labeled data. However, most works a…
NeRFuser: Large-Scale Scene Representation by NeRF Fusion
Jiading Fang, Shengjie Lin, Igor Vasiljevic +5
A practical benefit of implicit visual representations like Neural Radiance Fields (NeRFs) is their memory efficiency: large scenes can be efficiently stored and shared as small ne…
Viewpoint Equivariance for Multi-View 3D Object Detection
Dian Chen, Jie Li, Vitor Guizilini +2
3D object detection from visual sensors is a cornerstone capability of robotic systems. State-of-the-art methods focus on reasoning and decoding object bounding boxes from multi-vi…
DeLiRa: Self-Supervised Depth, Light, and Radiance Fields
Vitor Guizilini, Igor Vasiljevic, Jiading Fang +4
Differentiable volumetric rendering is a powerful paradigm for 3D reconstruction and novel view synthesis. However, standard volume rendering approaches struggle with degenerate ge…
Object Discovery from Motion-Guided Tokens
Zhipeng Bao, Pavel Tokmakov, Yu-Xiong Wang +2
Object discovery -- separating objects from the background without manual labels -- is a fundamental open challenge in computer vision. Previous methods struggle to go beyond clust…