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Found 11 papers, 7 papers with code
HeightFormer: Explicit Height Modeling without Extra Data for Camera-only 3D Object Detection in Bird's Eye View
In this work, we propose to explicitly model heights in the BEV space, which needs no extra data like LiDAR and can fit arbitrary camera rigs and types compared to modeling depths.
GaitMPL: Gait Recognition with Memory-Augmented Progressive Learning
In this work, we propose to solve the hard sample issue with a Memory-augmented Progressive Learning network (GaitMPL), including Dynamic Reweighting Progressive Learning module (DRPL) and Global Structure-Aligned Memory bank (GSAM).
UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View
Bird's eye view (BEV) representation is a new perception formulation for autonomous driving, which is based on spatial fusion.
Ultra Fast Deep Lane Detection with Hybrid Anchor Driven Ordinal Classification
With the help of the anchor-driven representation, we then reformulate the lane detection task as an ordinal classification problem to get the coordinates of lanes.
MonoGround: Detecting Monocular 3D Objects from the Ground
To alleviate this problem, we propose to introduce the ground plane as a prior in the monocular 3d object detection.
VersatileGait: A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation
To diversify the extrinsic factors of gait, we build a complicated scene with a dense camera layout.
VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios
With the motivation of practical gait recognition applications, we propose to automatically create a large-scale synthetic gait dataset (called VersatileGait) by a game engine, which consists of around one million silhouette sequences of 11, 000 subjects with fine-grained attributes in various complicated scenarios.
RDI-Net: Relational Dynamic Inference Networks
In this paper, we model the relations for dynamic inference from two aspects: the routers and the samples.
FcaNet: Frequency Channel Attention Networks
With the proof, we naturally generalize the compression of the channel attention mechanism in the frequency domain and propose our method with multi-spectral channel attention, termed as FcaNet.
CoDiNet: Path Distribution Modeling with Consistency and Diversity for Dynamic Routing
In this paper, we see dynamic routing networks in a fresh light, formulating a routing method as a mapping from a sample space to a routing space.
Ultra Fast Structure-aware Deep Lane Detection
Modern methods mainly regard lane detection as a problem of pixel-wise segmentation, which is struggling to address the problem of challenging scenarios and speed.
Ranked #48 on
Lane Detection
on CULane
