6 papers
OneStory: Coherent Multi-Shot Video Generation with Adaptive Memory
Zhaochong An, Menglin Jia, Haonan Qiu +12
Storytelling in real-world videos often unfolds through multiple shots -- discontinuous yet semantically connected clips that together convey a coherent narrative. However, existin…
Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model
Zhaochong An, Guolei Sun, Yun Liu +4
Generalized few-shot 3D point cloud segmentation (GFS-PCS) adapts models to new classes with few support samples while retaining base class segmentation. Existing GFS-PCS methods e…
Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation
Zhaochong An, Guolei Sun, Yun Liu +5
Few-shot 3D point cloud segmentation (FS-PCS) aims at generalizing models to segment novel categories with minimal annotated support samples. While existing FS-PCS methods have sho…
Coarse-To-Fine Tensor Trains for Compact Visual Representations
Sebastian Loeschcke, Dan Wang, Christian Leth-Espensen +3
The ability to learn compact, high-quality, and easy-to-optimize representations for visual data is paramount to many applications such as novel view synthesis and 3D reconstructio…
LoQT: Low-Rank Adapters for Quantized Pretraining
Sebastian Loeschcke, Mads Toftrup, Michael J. Kastoryano +2
Despite advances using low-rank adapters and quantization, pretraining of large models on consumer hardware has not been possible without model sharding, offloading during training…
Rethinking Few-shot 3D Point Cloud Semantic Segmentation
Zhaochong An, Guolei Sun, Yun Liu +5
This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS), with a focus on two significant issues in the state-of-the-art: foreground leakage and sparse point dist…