Search Results for author:
Found 14 papers, 4 papers with code
DifFUSER: Diffusion Model for Robust Multi-Sensor Fusion in 3D Object Detection and BEV Segmentation
Diffusion models have recently gained prominence as powerful deep generative models, demonstrating unmatched performance across various domains.
JRDB-PanoTrack: An Open-world Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments
JRDB-PanoTrack includes (1) various data involving indoor and outdoor crowded scenes, as well as comprehensive 2D and 3D synchronized data modalities; (2) high-quality 2D spatial panoptic segmentation and temporal tracking annotations, with additional 3D label projections for further spatial understanding; (3) diverse object classes for closed- and open-world recognition benchmarks, with OSPA-based metrics for evaluation.
Open-Vocabulary Scene Text Recognition via Pseudo-Image Labeling and Margin Loss
In this paper, we propose a novel open-vocabulary text recognition framework, Pseudo-OCR, to recognize OOV words.
Unified Open-Vocabulary Dense Visual Prediction
We present a UOVN training mechanism to reduce such gaps.
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation
Moreover, a simple and effective relation regularization is proposed to ensure the longitudinal relations among the three outputs to improve the model learning.
Open-Vocabulary Object Detection via Scene Graph Discovery
However, they only use pairs of nouns and individual objects in VL data, while these data usually contain much more information, such as scene graphs, which are also crucial for OV detection.
Class Enhancement Losses with Pseudo Labels for Zero-shot Semantic Segmentation
Recent mask proposal models have significantly improved the performance of zero-shot semantic segmentation.
Transformer Scale Gate for Semantic Segmentation
Effectively encoding multi-scale contextual information is crucial for accurate semantic segmentation.
ProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues
Firstly, we analyze CLIP for unsupervised open-category proposal generation and design an objectness score based on our empirical analysis on proposal selection.
Unpaired Referring Expression Grounding via Bidirectional Cross-Modal Matching
To avoid the laborious annotation in conventional referring grounding, unpaired referring grounding is introduced, where the training data only contains a number of images and queries without correspondences.
Accurate and Real-time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network
Efficiently and accurately detecting people from 3D point cloud data is of great importance in many robotic and autonomous driving applications.
Deep Music Retrieval for Fine-Grained Videos by Exploiting Cross-Modal-Encoded Voice-Overs
In this paper, we also investigate the widely added voice-overs in short videos and propose a novel framework to retrieve BGM for fine-grained short videos.
Scene Parsing via Integrated Classification Model and Variance-Based Regularization
On the one hand, the integrated classification model contains multiple classifiers, not only the general classifier but also a refinement classifier to distinguish the confusing categories.
Ranked #1 on
Scene Segmentation
on SUN-RGBD
Key-Word-Aware Network for Referring Expression Image Segmentation
On the other hand, the relationships of different image regions are not considered as well, even though they are greatly important to eliminate the undesired foreground object in accordance with specific query.
