ReViV: Reconstructing the Viewer and the View in 4D from Monocular Egocentric Video

arXiv:2607.17790 · cs.CV, cs.AI · Submitted 2026-07-20 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-07-20

Updated: 2026-10-07

Project page: https://reviv4d.github.io

Terminology

Transformer — 28× in this paper · explained in 2 episodes
Accuracy — 19× in this paper · explained in 1 episode
Alignment — 14× in this paper · explained in 1 episode
Ablation — 13× in this paper · explained in 1 episode
Masked Generative Egocentric Transformer — 11× in this paper
Benchmark — 10× in this paper · explained in 2 episodes
Unified Framework — 7× in this paper · explained in 5 episodes
Embeddings — 6× in this paper · explained in 2 episodes
Generalization — 6× in this paper · explained in 13 episodes
Quantization — 6× in this paper · explained in 12 episodes
Tokenization — 6× in this paper · explained in 2 episodes
Aria Digital Twin — 5× in this paper
Conference on Computer Vision and Pattern Recognition — 5× in this paper
Core — 5× in this paper · explained in 2 episodes
Digital Twin — 5× in this paper · explained in 5 episodes
Fidelity — 5× in this paper · explained in 2 episodes
Gaussian Splatting — 4× in this paper · explained in 4 episodes
Latent Space — 4× in this paper · explained in 7 episodes
Ablation Studies — 3× in this paper · explained in 1 episode
CVF International Conference on Computer Vision — 3× in this paper
Multimodal Dataset — 3× in this paper · explained in 2 episodes
Point Clouds — 3× in this paper · explained in 2 episodes
Benchmarking — 2× in this paper · explained in 3 episodes
Consistency — 2× in this paper · explained in 3 episodes
Diffusion Model — 2× in this paper · explained in 8 episodes
Diffusion Models — 2× in this paper · explained in 6 episodes
Foundation Model — 2× in this paper · explained in 3 episodes
Generative Modeling — 2× in this paper · explained in 3 episodes
Latent Representation — 2× in this paper · explained in 2 episodes
Latent Representations — 2× in this paper · explained in 3 episodes
Mean Squared Error — 2× in this paper
Optical Flow — 2× in this paper · explained in 2 episodes
Pseudo-labels — 2× in this paper · explained in 2 episodes
Regularization — 2× in this paper · explained in 3 episodes
Semantic Alignment — 2× in this paper · explained in 3 episodes
3D Gaussian Splatting — 1× in this paper · explained in 2 episodes
Absolute Translation Error — 1× in this paper
AdamW Optimizer — 1× in this paper · explained in 1 episode
Attention Mechanism — 1× in this paper · explained in 3 episodes
Cosine Similarity — 1× in this paper · explained in 3 episodes
Decode — 1× in this paper · explained in 2 episodes
Embodied AI — 1× in this paper · explained in 2 episodes
Exponential Moving Average — 1× in this paper
Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
Foundation Models — 1× in this paper · explained in 7 episodes
Generalizability — 1× in this paper · explained in 6 episodes
Generative Model — 1× in this paper · explained in 2 episodes
Generative Models — 1× in this paper · explained in 2 episodes
Loss Function — 1× in this paper · explained in 2 episodes
Mean Per Joint Position Error — 1× in this paper
Multimodal Reasoning — 1× in this paper · explained in 5 episodes
Pseudo-labeling — 1× in this paper · explained in 3 episodes
Reconstruction Error — 1× in this paper · explained in 2 episodes
Reinforcement Learning — 1× in this paper · explained in 4 episodes
Relative Rotation Error — 1× in this paper
Relative Translation Error — 1× in this paper
Robustness — 1× in this paper · explained in 5 episodes
Transfer Learning — 1× in this paper · explained in 10 episodes
Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

ReViV: Reconstructing the Viewer and the View in 4D from Monocular Egocentric Video

Terminology

Sources

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