Search Results for author:
Found 26 papers, 11 papers with code
Learning at the Speed of Wireless: Online Real-Time Learning for AI-Enabled MIMO in NextG
At the air interface, multiple-input multiple-output (MIMO) and its variants such as multi-user MIMO (MU-MIMO) and massive/full-dimension MIMO have been key enablers across successive generations of cellular networks with evolving complexity and design challenges.
Pixel Aligned Language Models
When taking locations as inputs, the model performs location-conditioned captioning, which generates captions for the indicated object or region.
IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks
Given a textual description of a visual task (e. g. "Left: input image, Right: foreground segmentation"), a few input-output visual examples, or both, the model in-context learns to solve it for a new test input.
2D-RC: Two-Dimensional Neural Network Approach for OTFS Symbol Detection
Orthogonal time frequency space (OTFS) is a promising modulation scheme for wireless communication in high-mobility scenarios.
Learning to Estimate: A Real-Time Online Learning Framework for MIMO-OFDM Channel Estimation
In this paper we introduce StructNet-CE, a novel real-time online learning framework for MIMO-OFDM channel estimation, which only utilizes over-the-air (OTA) pilot symbols for online training and converges within one OFDM subframe.
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models
Our approach outperforms the previous state of the art by significant margins on both open-vocabulary panoptic and semantic segmentation tasks.
Ranked #2 on
Open-World Instance Segmentation
on UVO
(using extra training data)
Open Vocabulary Panoptic Segmentation
Open Vocabulary Semantic Segmentation
+4
GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
In each GP Block, features are first grouped together by a fixed number of learnable group tokens; we then perform Group Propagation where global information is exchanged between the grouped features; finally, global information in the updated grouped features is returned back to the image features through a transformer decoder.
Detect to Learn: Structure Learning with Attention and Decision Feedback for MIMO-OFDM Receive Processing
The DF mechanism further enhances detection performance by dynamically tracking the channel changes through detected data symbols.
Learning Implicit Feature Alignment Function for Semantic Segmentation
As such, IFA implicitly aligns the feature maps at different levels and is capable of producing segmentation maps in arbitrary resolutions.
GroupViT: Semantic Segmentation Emerges from Text Supervision
With only text supervision and without any pixel-level annotations, GroupViT learns to group together semantic regions and successfully transfers to the task of semantic segmentation in a zero-shot manner, i. e., without any further fine-tuning.
RC-Struct: A Structure-based Neural Network Approach for MIMO-OFDM Detection
The binary classifier enables the efficient utilization of the precious online training symbols and allows an easy extension to high-order modulations without a substantial increase in complexity.
Learning to Equalize OTFS
Orthogonal Time Frequency Space (OTFS) is a novel framework that processes modulation symbols via a time-independent channel characterized by the delay-Doppler domain.
Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time
Estimating 3D hand and object pose from a single image is an extremely challenging problem: hands and objects are often self-occluded during interactions, and the 3D annotations are scarce as even humans cannot directly label the ground-truths from a single image perfectly.
Ranked #7 on
hand-object pose
on HO-3D
Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective
To learn generalizable representation for correspondence in large-scale, a variety of self-supervised pretext tasks are proposed to explicitly perform object-level or patch-level similarity learning.
Harnessing Tensor Structures -- Multi-Mode Reservoir Computing and Its Application in Massive MIMO
In this paper, we introduce a new neural network (NN) structure, multi-mode reservoir computing (Multi-Mode RC).
P4Neighbor: Efficient Link Failure Recovery With Programmable Switches
In this article, we analyze why implementing traditional proactive failure recovery mechanism introduces huge switch storage overhead, and discuss the flexibility and limitations of the programmable data plane.
Estimation of Number of Communities in Assortative Sparse Networks
Most community detection algorithms assume the number of communities, K, to be known a priori.
Global Context Networks
The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range dependencies within an image, via aggregating query-specific global context to each query position.
Ranked #40 on
Instance Segmentation
on COCO test-dev
DRG: Dual Relation Graph for Human-Object Interaction Detection
We tackle the challenging problem of human-object interaction (HOI) detection.
Ranked #26 on
Human-Object Interaction Detection
on V-COCO
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching
Significant progress has been made in Video Object Segmentation (VOS), the video object tracking task in its finest level.
Ranked #71 on
Semi-Supervised Video Object Segmentation
on DAVIS 2016
Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories
We address the problem of discovering 3D parts for objects in unseen categories.
MMDetection: Open MMLab Detection Toolbox and Benchmark
In this paper, we introduce the various features of this toolbox.
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
In this paper, we take advantage of this finding to create a simplified network based on a query-independent formulation, which maintains the accuracy of NLNet but with significantly less computation.
Ranked #25 on
Object Detection
on COCO-O
Spatial-Temporal Relation Networks for Multi-Object Tracking
Recent progress in multiple object tracking (MOT) has shown that a robust similarity score is key to the success of trackers.
Deep High Dynamic Range Imaging with Large Foreground Motions
In state-of-the-art deep HDR imaging, input images are first aligned using optical flows before merging, which are still error-prone due to occlusion and large motions.
STCP: Simplified-Traditional Chinese Conversion and Proofreading
This paper aims to provide an effective tool for conversion between Simplified Chinese and Traditional Chinese.
