Search Results for author:
Found 8 papers, 1 papers with code
Enhancing Person Re-Identification via Uncertainty Feature Fusion and Wise Distance Aggregation
The quest for robust Person re-identification (Re-ID) systems capable of accurately identifying subjects across diverse scenarios remains a formidable challenge in surveillance and security applications.
TwinLiteNetPlus: A Stronger Model for Real-time Drivable Area and Lane Segmentation
Semantic segmentation is crucial for autonomous driving, particularly for Drivable Area and Lane Segmentation, ensuring safety and navigation.
Ranked #1 on
Lane Detection
on BDD100K val
(IoU (%) metric)
Efficient Finetuning Large Language Models For Vietnamese Chatbot
Furthermore, the availability of pretrained LLMs and instruction-tune datasets for Vietnamese language is limited.
Few-Shot Object Detection via Synthetic Features with Optimal Transport
Our overarching goal is to train a generator that captures the data variations of the base dataset.
Instance-level Few-shot Learning with Class Hierarchy Mining
In this paper, we exploit the hierarchical information to leverage discriminative and relevant features of base classes to effectively classify novel objects.
The Art of Camouflage: Few-shot Learning for Animal Detection and Segmentation
In this paper, we address the problem of few-shot learning for camouflaged object detection and segmentation.
SketchANIMAR: Sketch-based 3D Animal Fine-Grained Retrieval
To this end, we introduce a novel SHREC challenge track that focuses on retrieving relevant 3D animal models from a dataset using sketch queries and expedites accessing 3D models through available sketches.
TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval
Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval.
