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Found 20 papers, 15 papers with code
Referring Flexible Image Restoration
These situations and requirements shed light on a new challenge in image restoration, where a model must perceive and remove specific degradation types specified by human commands in images with multiple degradations.
WaterVG: Waterway Visual Grounding based on Text-Guided Vision and mmWave Radar
The pattern of text-guided two sensors equips a finer granularity of text prompts with visual and radar features of referred targets.
Achelous++: Power-Oriented Water-Surface Panoptic Perception Framework on Edge Devices based on Vision-Radar Fusion and Pruning of Heterogeneous Modalities
Urban water-surface robust perception serves as the foundation for intelligent monitoring of aquatic environments and the autonomous navigation and operation of unmanned vessels, especially in the context of waterway safety.
Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Review
This review focuses on exploring different radar data representations utilized in autonomous driving systems.
Efficient-VRNet: An Exquisite Fusion Network for Riverway Panoptic Perception based on Asymmetric Fair Fusion of Vision and 4D mmWave Radar
In this paper, we focus on riverway panoptic perception based on USVs, which is a considerably unexplored field compared with road panoptic perception.
Achelous: A Fast Unified Water-surface Panoptic Perception Framework based on Fusion of Monocular Camera and 4D mmWave Radar
Current perception models for different tasks usually exist in modular forms on Unmanned Surface Vehicles (USVs), which infer extremely slowly in parallel on edge devices, causing the asynchrony between perception results and USV position, and leading to error decisions of autonomous navigation.
Ranked #1 on
2D Semantic Segmentation
on WaterScenes
WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmark for Autonomous Driving on Water Surfaces
This work presents WaterScenes, the first multi-task 4D radar-camera fusion dataset for autonomous driving on water surfaces.
Ranked #1 on
Object Detection
on WaterScenes
FindVehicle and VehicleFinder: A NER dataset for natural language-based vehicle retrieval and a keyword-based cross-modal vehicle retrieval system
Natural language (NL) based vehicle retrieval is a task aiming to retrieve a vehicle that is most consistent with a given NL query from among all candidate vehicles.
Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review
Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surrounding environment for safe and efficient navigation.
Large-Scale Traffic Signal Control Using Constrained Network Partition and Adaptive Deep Reinforcement Learning
However, the existing partitioning rules either have no constraints on the topology of regions or require the same topology for all regions.
Fully and Weakly Supervised Referring Expression Segmentation with End-to-End Learning
To validate our framework on a weakly-supervised setting, we annotated three RES benchmark datasets (RefCOCO, RefCOCO+ and RefCOCOg) with click annotations. Our method is simple but surprisingly effective, outperforming all previous state-of-the-art RES methods on fully- and weakly-supervised settings by a large margin.
Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detection
To achieve this, we design a democratic prototype generation module to generate democratic response maps, covering sufficient co-salient regions and thereby involving more shared attributes of co-salient objects.
Ranked #3 on
Co-Salient Object Detection
on CoCA
Fast Pixel-Matching for Video Object Segmentation
Most mask-propagation based models are faster but with relatively low performance due to failure to adapt to object appearance variation.
Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
In this paper, we are tackling the weakly-supervised referring expression grounding task, for the localization of a referent object in an image according to a query sentence, where the mapping between image regions and queries are not available during the training stage.
Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning
In this paper, we are tackling the proposal-free referring expression grounding task, aiming at localizing the target object according to a query sentence, without relying on off-the-shelf object proposals.
Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence
Since scribble labels fail to offer detailed salient regions, we propose a local coherence loss to propagate the labels to unlabeled regions based on image features and pixel distance, so as to predict integral salient regions with complete object structures.
A Semi-Blind Multiuser SIMO GFDM System in the Presence of CFOs and IQ Imbalances
A low-complexity semi-blind joint estimation scheme of multiple channels, CFOs and IQ imbalances is proposed.
Fast Template Matching and Update for Video Object Tracking and Segmentation
Specifically, the reinforcement learning agent learns to decide whether to update the target template according to the quality of the predicted result.
Progressive Sample Mining and Representation Learning for One-Shot Person Re-identification with Adversarial Samples
To tackle this problem, we propose to iteratively guess pseudo labels for the unlabeled image samples, which are later used to update the re-identification model together with the labelled samples.
Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning
In this paper, we aim to tackle the task of semi-supervised video object segmentation across a sequence of frames where only the ground-truth segmentation of the first frame is provided.
