154 citations · 605 across the 50 of their papers we have counts for
61 papers
Lite Any Stereo V2: Faster and Stronger Efficient Zero-Shot Stereo Matching
Junpeng Jing, Ronglai Zuo, Zhelun Shen +5
Recent advances in stereo matching have achieved remarkable accuracy, but often rely on large models, heavy computation, or additional foundation-model priors, making them difficul…
RGB-Pointmap Pretraining for Unified 3D Scene Understanding
Ye Mao, Weixun Luo, Ranran Huang +2
Pretraining 3D encoders through alignment with Contrastive Language-Image Pre-training (CLIP) has emerged as a promising direction for learning generalizable representations for 3D…
From None to All: Self-Supervised 3D Reconstruction via Novel View Synthesis
Ranran Huang, Weixun Luo, Ye Mao +1
In this paper, we introduce NAS3R, a self-supervised feed-forward framework that jointly learns explicit 3D geometry and camera parameters with no ground-truth annotations and no p…
Diffusion-aided Extreme Video Compression with Lightweight Semantics Guidance
Maojun Zhang, Haotian Wu, Richeng Jin +2
Modern video codecs and learning-based approaches struggle for semantic reconstruction at extremely low bit-rates due to reliance on low-level spatiotemporal redundancies. Generati…
POMA-3D: The Point Map Way to 3D Scene Understanding
Ye Mao, Weixun Luo, Ranran Huang +2
In this paper, we introduce POMA-3D, the first self-supervised 3D representation model learned from point maps. Point maps encode explicit 3D coordinates on a structured 2D grid, p…
Lite Any Stereo: Efficient Zero-Shot Stereo Matching
Junpeng Jing, Weixun Luo, Ye Mao +1
Recent advances in stereo matching have focused on accuracy, often at the cost of significantly increased model size. Traditionally, the community has regarded efficient models as…