31 citations · 42 across the 15 of their papers we have counts for
16 papers
ResCLIP: Few-Shot Generalist Anomaly Detection with Residual-to-Residual Alignment
Xinyue Liu, Jianyuan Wang, Biao Leng +1
Few-shot Generalist Anomaly Detection requires models to generalize to novel categories without retraining, posing significant challenges in real-world scenarios with scarce sample…
VGGT-
Jianyuan Wang, Minghao Chen, Shangzhan Zhang +7
Recent feed-forward reconstruction models, such as VGGT, have proven competitive with traditional optimization-based reconstructors while also providing geometry-aware features use…
SceneScribe-1M: A Large-Scale Video Dataset with Comprehensive Geometric and Semantic Annotations
Yunnan Wang, Kecheng Zheng, Jianyuan Wang +8
The convergence of 3D geometric perception and video synthesis has created an unprecedented demand for large-scale video data that is rich in both semantic and spatio-temporal info…
LagerNVS: Latent Geometry for Fully Neural Real-time Novel View Synthesis
Stanislaw Szymanowicz, Minghao Chen, Jianyuan Wang +2
Recent work has shown that neural networks can perform 3D tasks such as Novel View Synthesis (NVS) without explicit 3D reconstruction. Even so, we argue that strong 3D inductive bi…
LitePT: Lighter Yet Stronger Point Transformer
Yuanwen Yue, Damien Robert, Jianyuan Wang +4
Modern neural architectures for 3D point cloud processing contain both convolutional layers and attention blocks, but the best way to assemble them remains unclear. We analyse the…
DINOv3
Oriane Siméoni, Huy V. Vo, Maximilian Seitzer +23
Self-supervised learning holds the promise of eliminating the need for manual data annotation, enabling models to scale effortlessly to massive datasets and larger architectures. B…
AutoPartGen: Autogressive 3D Part Generation and Discovery
Minghao Chen, Jianyuan Wang, Roman Shapovalov +6
We introduce AutoPartGen, a model that generates objects composed of 3D parts in an autoregressive manner. This model can take as input an image of an object, 2D masks of the objec…
SpatialTrackerV2: 3D Point Tracking Made Easy
Yuxi Xiao, Jianyuan Wang, Nan Xue +7
We present SpatialTrackerV2, a feed-forward 3D point tracking method for monocular videos. Going beyond modular pipelines built on off-the-shelf components for 3D tracking, our app…
Advances in Feed-Forward 3D Reconstruction and View Synthesis: A Survey
Jiahui Zhang, Yuelei Li, Anpei Chen +15
3D reconstruction and view synthesis are foundational problems in computer vision, graphics, and immersive technologies such as augmented reality (AR), virtual reality (VR), and di…
VGGT: Visual Geometry Grounded Transformer
Jianyuan Wang, Minghao Chen, Nikita Karaev +3
We present VGGT, a feed-forward neural network that directly infers all key 3D attributes of a scene, including camera parameters, point maps, depth maps, and 3D point tracks, from…
FLARE: Feed-forward Geometry, Appearance and Camera Estimation from Uncalibrated Sparse Views
Shangzhan Zhang, Jianyuan Wang, Yinghao Xu +5
We present FLARE, a feed-forward model designed to infer high-quality camera poses and 3D geometry from uncalibrated sparse-view images (i.e., as few as 2-8 inputs), which is a cha…
UnCommon Objects in 3D
Xingchen Liu, Piyush Tayal, Jianyuan Wang +10
We introduce Uncommon Objects in 3D (uCO3D), a new object-centric dataset for 3D deep learning and 3D generative AI. uCO3D is the largest publicly-available collection of high-reso…
PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models
Minghao Chen, Roman Shapovalov, Iro Laina +4
Text- or image-to-3D generators and 3D scanners can now produce 3D assets with high-quality shapes and textures. These assets typically consist of a single, fused representation, l…
CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos
Nikita Karaev, Iurii Makarov, Jianyuan Wang +3
Most state-of-the-art point trackers are trained on synthetic data due to the difficulty of annotating real videos for this task. However, this can result in suboptimal performance…
Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation
Junlin Han, Jianyuan Wang, Andrea Vedaldi +2
Generating high-quality 3D content from text, single images, or sparse view images remains a challenging task with broad applications. Existing methods typically employ multi-view…
Visual Geometry Grounded Deep Structure From Motion
Jianyuan Wang, Nikita Karaev, Christian Rupprecht +1
Structure-from-motion (SfM) is a long-standing problem in the computer vision community, which aims to reconstruct the camera poses and 3D structure of a scene from a set of uncons…