activity
20212026
most citedLiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation

3 citations · 3 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Unravel: Recovering an Interactive 3D Scene from a Single Image

Hui Shan, Keyang Luo, Binjia Zhou +10

We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable asset. Existing generators ei…

cs.CV2026

Scenix: Sparse-View 3D Scene Reconstruction via Executable Scene Programs

Kai Li, Lutao Jiang, Zhenyang Li +10

Synthesizing a structured and editable 3D indoor scene from a few uncalibrated RGB views requires more than generating high-quality individual assets: a system must infer the room…

cs.CV2026

MSVS-VAE: Multi-Scale Anchored VecSet for High-Fidelity 3D Reconstruction

Dehao Hao, Kaiyi Zhang, Tanghui Jia +10

High-fidelity 3D generative modeling increasingly relies on the latent diffusion paradigm, where the reconstruction quality of the underlying 3D VAE becomes a primary bottleneck. E…

cs.CV2026

SAP: Segment Any 4K Panorama

Lutao Jiang, Zidong Cao, Weikai Chen +14

Promptable instance segmentation is widely adopted in embodied and AR systems, yet the performance of foundation models trained on perspective imagery often degrades on 360° panora…

cs.CV2026

CanoVerse: 3D Object Scalable Canonicalization and Dataset for Generation and Pose

Li Jin, Yuchen Yang, Weikai Chen +11

3D learning systems implicitly assume that objects occupy a coherent reference frame. Nonetheless, in practice, every asset arrives with an arbitrary global rotation, and models ar…

cs.CV2026

CoSMo3D: Open-World Promptable 3D Semantic Part Segmentation through LLM-Guided Canonical Spatial Modeling

Li Jin, Weikai Chen, Yujie Wang +7

Open-world promptable 3D semantic segmentation remains brittle as semantics are inferred in the input sensor coordinates. Yet, humans, in contrast, interpret parts via functional r…