activity
20242026
most citedParameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning

2 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

Xiao Luo, Mingyang Du, Xin Zhou +5

High-fidelity 3D generation predominantly relies on scaling model capacity and data, which incurs prohibitive computational costs. This paradigm typically requires learning geometr…

cs.CV2026

Infinite Worlds with Versatile Interactions

Zelin Gao, Qiuyu Wang, Jiapeng Zhu +17

We present LingBot-World 2.0 (also known as LingBot-World-Infinity), an advanced iteration of LingBot-World featuring four distinct upgrades. (1) Our model achieves an unbounded in…

cs.CV2026

PointTPA: Dynamic Network Parameter Adaptation for 3D Scene Understanding

Siyuan Liu, Chaoqun Zheng, Xin Zhou +3

Scene-level point cloud understanding remains challenging due to diverse geometries, imbalanced category distributions, and highly varied spatial layouts. Existing methods improve…

cs.CV2026

Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding

Xianjin Wu, Dingkang Liang, Tianrui Feng +5

While Multimodal Large Language Models demonstrate impressive semantic capabilities, they often suffer from spatial blindness, struggling with fine-grained geometric reasoning and…

cs.CV2025

SoccerNet 2025 Challenges Results

Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115

The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…

cs.CV2025

Less is Enough: Training-Free Video Diffusion Acceleration via Runtime-Adaptive Caching

Xin Zhou, Dingkang Liang, Kaijin Chen +7

Video generation models have demonstrated remarkable performance, yet their broader adoption remains constrained by slow inference speeds and substantial computational costs, prima…