57 citations · 108 across the 25 of their papers we have counts for
10 papers · 1 filter
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…
Rethinking Image Super-Resolution from Training Data Perspectives
Go Ohtani, Ryu Tadokoro, Ryosuke Yamada +7
In this work, we investigate the understudied effect of the training data used for image super-resolution (SR). Most commonly, novel SR methods are developed and benchmarked on com…
Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs
Brandon Smart, Chuanxia Zheng, Iro Laina +1
In this paper, we introduce Splatt3R, a pose-free, feed-forward method for in-the-wild 3D reconstruction and novel view synthesis from stereo pairs. Given uncalibrated natural imag…
Scaling Backwards: Minimal Synthetic Pre-training?
Ryo Nakamura, Ryu Tadokoro, Ryosuke Yamada +6
Pre-training and transfer learning are an important building block of current computer vision systems. While pre-training is usually performed on large real-world image datasets, i…
3D-Aware Instance Segmentation and Tracking in Egocentric Videos
Yash Bhalgat, Vadim Tschernezki, Iro Laina +3
Egocentric videos present unique challenges for 3D scene understanding due to rapid camera motion, frequent object occlusions, and limited object visibility. This paper introduces…
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
Xianzheng Ma, Brandon Smart, Yash Bhalgat +14
As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interact…