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Found 11 papers, 3 papers with code
IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding
Despite achieving rapid developments and with widespread applications, Large Vision-Language Models (LVLMs) confront a serious challenge of being prone to generating hallucinations.
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner
This pioneering work lays the groundwork for future research in semi-supervised learning for referring expression segmentation.
LLaFS: When Large Language Models Meet Few-Shot Segmentation
This paper proposes LLaFS, the first attempt to leverage large language models (LLMs) in few-shot segmentation.
Deep3DSketch+: Rapid 3D Modeling from Single Free-hand Sketches
In this work, we introduce a novel end-to-end approach, Deep3DSketch+, which performs 3D modeling using only a single free-hand sketch without inputting multiple sketches or view information.
PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes
Moreover, PanopticNeRF-360 enables omnidirectional rendering of high-fidelity, multi-view and spatiotemporally consistent appearance, semantic and instance labels.
Learning Gabor Texture Features for Fine-Grained Recognition
We innovatively utilize Gabor filters as a powerful extractor to exploit texture features, motivated by the capability of Gabor filters in effectively capturing multi-frequency features and detailed local information.
Dyn-E: Local Appearance Editing of Dynamic Neural Radiance Fields
We extensively evaluate our approach on various scenes and show that our approach achieves spatially and temporally consistent editing results.
SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More
We can even outperform task-specific network models and achieve state-of-the-art performance in the task we tested: camouflaged object detection, shadow detection.
Continual Semantic Segmentation with Automatic Memory Sample Selection
Continual Semantic Segmentation (CSS) extends static semantic segmentation by incrementally introducing new classes for training.
Painting 3D Nature in 2D: View Synthesis of Natural Scenes from a Single Semantic Mask
We introduce a novel approach that takes a single semantic mask as input to synthesize multi-view consistent color images of natural scenes, trained with a collection of single images from the Internet.
Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation
In this work, we present a novel 3D-to-2D label transfer method, Panoptic NeRF, which aims for obtaining per-pixel 2D semantic and instance labels from easy-to-obtain coarse 3D bounding primitives.
