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Found 15 papers, 12 papers with code
VoxGenesis: Unsupervised Discovery of Latent Speaker Manifold for Speech Synthesis
This forces the model to learn a speaker distribution disentangled from the semantic content.
ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention
Window-based transformers have demonstrated strong ability in large-scale point cloud understanding by capturing context-aware representations with affordable attention computation in a more localized manner.
Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution
To ensure the content consistency among adjacent frames, we exploit the temporal dynamics in LR videos to guide the diffusion process by optimizing the latent sampling path with a motion-guided loss, ensuring that the generated HR video maintains a coherent and continuous visual flow.
Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations
Self-supervised learning (SSL) speech models such as wav2vec and HuBERT have demonstrated state-of-the-art performance on automatic speech recognition (ASR) and proved to be extremely useful in low label-resource settings.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
One-to-Few Label Assignment for End-to-End Dense Detection
The positive and negative weights of these soft anchors are dynamically adjusted during training so that they can contribute more to ``representation learning'' in the early training stage, and contribute more to ``duplicated prediction removal'' in the later stage.
MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequences
Current top-performing multi-frame detectors mostly follow a Detect-and-Fuse framework, which extracts features from each frame of the sequence and fuses them to detect the objects in the current frame.
SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentation
Weakly supervised instance segmentation using only bounding box annotations has recently attracted much research attention.
DynaMask: Dynamic Mask Selection for Instance Segmentation
The representative instance segmentation methods mostly segment different object instances with a mask of the fixed resolution, e. g., 28*28 grid.
Masked Surfel Prediction for Self-Supervised Point Cloud Learning
In this work, we make the first attempt, to the best of our knowledge, to consider the local geometry information explicitly into the masked auto-encoding, and propose a novel Masked Surfel Prediction (MaskSurf) method.
Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds
VoxSeT is built upon a voxel-based set attention (VSA) module, which reduces the self-attention in each voxel by two cross-attentions and models features in a hidden space induced by a group of latent codes.
A Dual Weighting Label Assignment Scheme for Object Detection
Existing LA methods mostly focus on the design of pos weighting function, while the neg weight is directly derived from the pos weight.
Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation
One popular solution to this challenging task is self-training, which selects high-scoring predictions on target samples as pseudo labels for training.
Ranked #9 on
Image-to-Image Translation
on SYNTHIA-to-Cityscapes
Aug3D-RPN: Improving Monocular 3D Object Detection by Synthetic Images with Virtual Depth
Current geometry-based monocular 3D object detection models can efficiently detect objects by leveraging perspective geometry, but their performance is limited due to the absence of accurate depth information.
Structure Aware Single-Stage 3D Object Detection From Point Cloud
The auxiliary network is jointly optimized, by two point-level supervisions, to guide the convolutional features in the backbone network to be aware of the object structure.
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel-level by a human-machine hybrid algorithm (https://osf. io/nqjyw/, https://osf. io/t98fz/).
