334 citations · 883 across the 97 of their papers we have counts for
17 papers · 1 filter
Burn After Reading: Online Adaptation for Cross-domain Streaming Data
Luyu Yang, Mingfei Gao, Zeyuan Chen +3
In the context of online privacy, many methods propose complex privacy and security preserving measures to protect sensitive data. In this paper, we argue that: not storing any sen…
Dual-Key Multimodal Backdoors for Visual Question Answering
Matthew Walmer, Karan Sikka, Indranil Sur +2
The success of deep learning has enabled advances in multimodal tasks that require non-trivial fusion of multiple input domains. Although multimodal models have shown potential in…
PatchGame: Learning to Signal Mid-level Patches in Referential Games
Kamal Gupta, Gowthami Somepalli, Anubhav Gupta +3
We study a referential game (a type of signaling game) where two agents communicate with each other via a discrete bottleneck to achieve a common goal. In our referential game, the…
A Frequency Perspective of Adversarial Robustness
Shishira R Maiya, Max Ehrlich, Vatsal Agarwal +3
Adversarial examples pose a unique challenge for deep learning systems. Despite recent advances in both attacks and defenses, there is still a lack of clarity and consensus in the…
NeRV: Neural Representations for Videos
Hao Chen, Bo He, Hanyu Wang +3
We propose a novel neural representation for videos (NeRV) which encodes videos in neural networks. Unlike conventional representations that treat videos as frame sequences, we rep…
HR-RCNN: Hierarchical Relational Reasoning for Object Detection
Hao Chen, Abhinav Shrivastava
Incorporating relational reasoning in neural networks for object recognition remains an open problem. Although many attempts have been made for relational reasoning, they generally…
Diverse Video Generation using a Gaussian Process Trigger
Gaurav Shrivastava, Abhinav Shrivastava
Generating future frames given a few context (or past) frames is a challenging task. It requires modeling the temporal coherence of videos and multi-modality in terms of diversity…
No-frills Dynamic Planning using Static Planners
Mara Levy, Vasista Ayyagari, Abhinav Shrivastava
In this paper, we address the task of interacting with dynamic environments where the changes in the environment are independent of the agent. We study this through the context of…
Learning to Predict Visual Attributes in the Wild
Khoi Pham, Kushal Kafle, Zhe Lin +4
Visual attributes constitute a large portion of information contained in a scene. Objects can be described using a wide variety of attributes which portray their visual appearance…
Rethinking Pseudo Labels for Semi-Supervised Object Detection
Hengduo Li, Zuxuan Wu, Abhinav Shrivastava +1
Recent advances in semi-supervised object detection (SSOD) are largely driven by consistency-based pseudo-labeling methods for image classification tasks, producing pseudo labels a…
Towards Discovery and Attribution of Open-world GAN Generated Images
Sharath Girish, Saksham Suri, Saketh Rambhatla +1
With the recent progress in Generative Adversarial Networks (GANs), it is imperative for media and visual forensics to develop detectors which can identify and attribute images to…
The Pursuit of Knowledge: Discovering and Localizing Novel Categories using Dual Memory
Sai Saketh Rambhatla, Rama Chellappa, Abhinav Shrivastava
We tackle object category discovery, which is the problem of discovering and localizing novel objects in a large unlabeled dataset. While existing methods show results on datasets…
Learned Spatial Representations for Few-shot Talking-Head Synthesis
Moustafa Meshry, Saksham Suri, Larry S. Davis +1
We propose a novel approach for few-shot talking-head synthesis. While recent works in neural talking heads have produced promising results, they can still produce images that do n…
StEP: Style-based Encoder Pre-training for Multi-modal Image Synthesis
Moustafa Meshry, Yixuan Ren, Larry S Davis +1
We propose a novel approach for multi-modal Image-to-image (I2I) translation. To tackle the one-to-many relationship between input and output domains, previous works use complex tr…
Knowledge Evolution in Neural Networks
Ahmed Taha, Abhinav Shrivastava, Larry Davis
Deep learning relies on the availability of a large corpus of data (labeled or unlabeled). Thus, one challenging unsettled question is: how to train a deep network on a relatively…
SVMax: A Feature Embedding Regularizer
Ahmed Taha, Alex Hanson, Abhinav Shrivastava +1
A neural network regularizer (e.g., weight decay) boosts performance by explicitly penalizing the complexity of a network. In this paper, we penalize inferior network activations -…
Deep Video Inpainting Detection
Peng Zhou, Ning Yu, Zuxuan Wu +3
This paper studies video inpainting detection, which localizes an inpainted region in a video both spatially and temporally. In particular, we introduce VIDNet, Video Inpainting De…