activity
20242026
collaborators

9 papers

cs.CV2026

MoonSeg3R: Monocular Online Zero-Shot Segment Anything in 3D with Reconstructive Foundation Priors

Zhipeng Du, Duolikun Danier, Jan Eric Lenssen +1

In this paper, we focus on online zero-shot monocular 3D instance segmentation, a novel practical setting where existing approaches fail to perform because they rely on posed RGB-D…

cs.RO2026

Attentive Feature Aggregation or: How Policies Learn to Stop Worrying about Robustness and Attend to Task-Relevant Visual Cues

Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +4

The adoption of pre-trained visual representations (PVRs), leveraging features from large-scale vision models, has become a popular paradigm for training visuomotor policies. Howev…

cs.AI2026

SAM3-LiteText: An Anatomical Study of the SAM3 Text Encoder for Efficient Vision-Language Segmentation

Chengxi Zeng, Yuxuan Jiang, Ge Gao +6

Vision-language segmentation models such as SAM3 enable flexible, prompt-driven visual grounding, but inherit large, general-purpose text encoders originally designed for open-ende…

cs.CV2025

View-Consistent Diffusion Representations for 3D-Consistent Video Generation

Duolikun Danier, Ge Gao, Steven McDonagh +3

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated vid…

cs.RO2025

The Temporal Trap: Entanglement in Pre-Trained Visual Representations for Visuomotor Policy Learning

Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +2

The integration of pre-trained visual representations (PVRs) has significantly advanced visuomotor policy learning. However, effectively leveraging these models remains a challenge…

cs.CV2025

GFix: Perceptually Enhanced Gaussian Splatting Video Compression

Siyue Teng, Ge Gao, Duolikun Danier +5

3D Gaussian Splatting (3DGS) enhances 3D scene reconstruction through explicit representation and fast rendering, demonstrating potential benefits for various low-level vision task…