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Found 22 papers, 16 papers with code
HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras
Three-dimensional perception from multi-view cameras is a crucial component in autonomous driving systems, which involves multiple tasks like 3D object detection and bird's-eye-view (BEV) semantic segmentation.
Co-Speech Gesture Video Generation via Motion-Decoupled Diffusion Model
While previous works mostly generate structural human skeletons, resulting in the omission of appearance information, we focus on the direct generation of audio-driven co-speech gesture videos in this work.
RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detection
In the dual-stream radar backbone, a point-based encoder and a transformer-based encoder are proposed to extract radar features, with an injection and extraction module to facilitate communication between the two encoders.
Ranked #2 on
3D Object Detection
on nuscenes Camera-Radar
Few-Shot Adversarial Prompt Learning on Vision-Language Models
The vulnerability of deep neural networks to imperceptible adversarial perturbations has attracted widespread attention.
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective compositional text-to-3D generation.
LCV2: An Efficient Pretraining-Free Framework for Grounded Visual Question Answering
Experimental implementations were conducted under constrained computational and memory resources, evaluating the proposed method's performance on benchmark datasets including GQA, CLEVR, and VizWiz-VQA-Grounding.
Multi-view MidiVAE: Fusing Track- and Bar-view Representations for Long Multi-track Symbolic Music Generation
Variational Autoencoders (VAEs) constitute a crucial component of neural symbolic music generation, among which some works have yielded outstanding results and attracted considerable attention.
DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes
We present DrivingGaussian, an efficient and effective framework for surrounding dynamic autonomous driving scenes.
SAMPLING: Scene-adaptive Hierarchical Multiplane Images Representation for Novel View Synthesis from a Single Image
Recent novel view synthesis methods obtain promising results for relatively small scenes, e. g., indoor environments and scenes with a few objects, but tend to fail for unbounded outdoor scenes with a single image as input.
BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios
Based on the property of outdoor point clouds in autonomous driving scenarios, i. e., the point clouds of distant objects are more sparse, we propose point density prediction to enable the 3D encoder to learn location information, which is essential for object detection.
Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised Object Discovery with Transformers
Firstly, we present a foreground guidance strategy with an off-the-shelf UOD detector to highlight the foreground regions on the feature maps and then refine object locations in an iterative fashion.
FlowNAS: Neural Architecture Search for Optical Flow Estimation
To address this issue, we propose a neural architecture search method named FlowNAS to automatically find the better encoder architecture for flow estimation task.
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection
There are two critical sensors for 3D perception in autonomous driving, the camera and the LiDAR.
BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
Fusing the camera and LiDAR information has become a de-facto standard for 3D object detection tasks.
Continual Contrastive Learning for Image Classification
In this paper, we make the first attempt to tackle the catastrophic forgetting problem in the mainstream self-supervised methods, i. e., contrastive learning methods.
Outlier-Resilient Web Service QoS Prediction
The proliferation of Web services makes it difficult for users to select the most appropriate one among numerous functionally identical or similar service candidates.
Gated Task Interaction Framework for Multi-task Sequence Tagging
Others have shown that linguistic features can improve the performance of neural models on tasks such as chunking and named entity recognition (NER).
Composing Knowledge Graph Embeddings via Word Embeddings
As $(\mathbf{h},\mathbf{r},\mathbf{t})$ is learned from the existing facts within a knowledge graph, these representations can not be used to detect unknown facts (if the entities or relations never occur in the knowledge graph).
Quantifying consensus of rankings based on q-support patterns
Existing studies are insufficient in assessing the overall consensus of a ranking set.
Generative Neural Networks for Anomaly Detection in Crowded Scenes
Security surveillance is critical to social harmony and people's peaceful life.
Ranked #3 on
Abnormal Event Detection In Video
on UBI-Fights
Consensus measure of rankings
The consensus measure can be used to evaluate rankings in many information systems, as quite often there is not ground truth available for evaluation.
Concordance and the Smallest Covering Set of Preference Orderings
Preference orderings are orderings of a set of items according to the preferences (of judges).
