4 citations · 7 across the 6 of their papers we have counts for
7 papers
Partial CLIP is Enough: Chimera-Seg for Zero-shot Semantic Segmentation
Jialei Chen, Xu Zheng, Danda Pani Paudel +3
Zero-shot Semantic Segmentation (ZSS) aims to segment both seen and unseen classes using supervision from only seen classes. Beyond adaptation-based methods, distillation-based app…
BiXFormer: A Robust Framework for Maximizing Modality Effectiveness in Multi-Modal Semantic Segmentation
Jialei Chen, Xu Zheng, Danda Pani Paudel +3
Utilizing multi-modal data enhances scene understanding by providing complementary semantic and geometric information. Existing methods fuse features or distill knowledge from mult…
Split Matching for Inductive Zero-shot Semantic Segmentation
Jialei Chen, Xu Zheng, Dongyue Li +6
Zero-shot Semantic Segmentation (ZSS) aims to segment categories that are not annotated during training. While fine-tuning vision-language models has achieved promising results, th…
CQVPR: Landmark-aware Contextual Queries for Visual Place Recognition
Dongyue Li, Daisuke Deguchi, Hiroshi Murase
Visual Place Recognition (VPR) aims to estimate the location of the given query image within a database of geo-tagged images. To identify the exact location in an image, detecting…
Generalizable Semantic Vision Query Generation for Zero-shot Panoptic and Semantic Segmentation
Jialei Chen, Daisuke Deguchi, Chenkai Zhang +1
Zero-shot Panoptic Segmentation (ZPS) aims to recognize foreground instances and background stuff without images containing unseen categories in training. Due to the visual data sp…
CLIP Is Also a Good Teacher: A New Learning Framework for Inductive Zero-shot Semantic Segmentation
Jialei Chen, Daisuke Deguchi, Chenkai Zhang +2
Generalized Zero-shot Semantic Segmentation aims to segment both seen and unseen categories only under the supervision of the seen ones. To tackle this, existing methods adopt the…