Related papers: A Performance Evaluation of Nomon: A Flexible Inte…
Despite the promising high-data rate features of visible light communications (VLC), they still suffer from unbalanced services due to blockages and channel fluctuation among users. This paper introduces and evaluates a new transmission…
We propose Framer for interactive frame interpolation, which targets producing smoothly transitioning frames between two images as per user creativity. Concretely, besides taking the start and end frames as inputs, our approach supports…
When operated in the mmWave band, user channels get highly correlated which can be exploited in mmWave-NOMA systems to cluster a set of "correlated" users together. Identifying the set of users to cluster greatly affects the viability of…
While shared autonomy offers significant potential for assistive robotics, key questions remain about how to effectively map 2D control inputs to 6D robot motions. An intuitive framework should allow users to input commands effortlessly,…
Non-orthogonal multiple access (NOMA) has been widely nominated as an emerging spectral efficiency (SE) multiple access technique for the next generation of wireless communication network. To meet the growing demands in massive connectivity…
The accurate reconstruction of dynamic scenes with neural radiance fields is significantly dependent on the estimation of camera poses. Widely used structure-from-motion pipelines encounter difficulties in accurately tracking the camera…
Non-orthogonal multiple access (NOMA) serves multiple users by superposing their distinct message signals. The desired message signal is decoded at the receiver by applying successive interference cancellation (SIC). Using the theory of…
This paper proposes a new communication protocol for a cooperative non-orthogonal multiple access (NOMA) system. In this system, based on users' channel conditions, each two NOMA users are paired to reduce system complexity. In this…
For multimodal large language models (MLLMs), visual information is relatively sparse compared with text. As a result, research on visual pruning emerges for efficient inference. Current approaches typically measure token importance based…
Non-orthogonal multiple access (NOMA) allows users sharing a resource-block to efficiently reuse spectrum and improve cell sum rate $\mathcal{R}_{\rm tot}$ at the expense of increased interference. Orthogonal multiple access (OMA), on the…
The rapid progress of Large Multimodal Models (LMMs) and cloud-based AI agents is transforming human-AI collaboration into bidirectional, multimodal interaction. However, existing codecs remain optimized for unimodal, one-way communication,…
The development of the industrial Internet of Things (IoT) calls for higher spectrum efficiency (SE). Faster than Nyquist (FTN) and non-orthogonal multiple access (NOMA) are both promising paradigms to improve the SE without any extra…
Activity recognition computer vision algorithms can be used to detect the presence of autism-related behaviors, including what are termed "restricted and repetitive behaviors", or stimming, by diagnostic instruments. The limited data that…
The need to count and localize repeating objects in an image arises in different scenarios, such as biological microscopy studies, production lines inspection, and surveillance recordings analysis. The use of supervised Convoutional Neural…
Current vision models typically maintain a fixed correspondence between their representation structure and image space. Each layer comprises a set of tokens arranged "on-the-grid," which biases patches or tokens to encode information at a…
Co-Salient Object Detection (CoSOD) aims at simulating the human visual system to discover the common and salient objects from a group of relevant images. Recent methods typically develop sophisticated deep learning based models have…
Non-orthogonal multiple access (NOMA) has gained significant attention as a potential next-generation multiple access technique. However, its implementation with finite-alphabet inputs faces challenges. Particularly, due to inter-user…
3D object detection with surrounding cameras has been a promising direction for autonomous driving. In this paper, we present SimMOD, a Simple baseline for Multi-camera Object Detection, to solve the problem. To incorporate multi-view…
We present ASSIST, an object-wise neural radiance field as a panoptic representation for compositional and realistic simulation. Central to our approach is a novel scene node data structure that stores the information of each object in a…
Anomaly detection on attributed networks is widely used in online shopping, financial transactions, communication networks, and so on. However, most existing works trying to detect anomalies on attributed networks only consider a single…