10 citations · 11 across the 8 of their papers we have counts for
9 papers
Action100M: A Large-scale Video Action Dataset
Delong Chen, Tejaswi Kasarla, Yejin Bang +6
Inferring physical actions from visual observations is a fundamental capability for advancing machine intelligence in the physical world. Achieving this requires large-scale, open-…
VL-JEPA: Joint Embedding Predictive Architecture for Vision-language
Delong Chen, Mustafa Shukor, Theo Moutakanni +7
We introduce VL-JEPA, a vision-language model built on a Joint Embedding Predictive Architecture (JEPA). Instead of autoregressively generating tokens as in classical VLMs, VL-JEPA…
Balanced Hyperbolic Embeddings Are Natural Out-of-Distribution Detectors
Tejaswi Kasarla, Max van Spengler, Pascal Mettes
Out-of-distribution recognition forms an important and well-studied problem in deep learning, with the goal to filter out samples that do not belong to the distribution on which a…
Hyperbolic Safety-Aware Vision-Language Models
Tobia Poppi, Tejaswi Kasarla, Pascal Mettes +2
Addressing the retrieval of unsafe content from vision-language models such as CLIP is an important step towards real-world integration. Current efforts have relied on unlearning t…
Maximally Separated Active Learning
Tejaswi Kasarla, Abhishek Jha, Faye Tervoort +2
Active Learning aims to optimize performance while minimizing annotation costs by selecting the most informative samples from an unlabelled pool. Traditional uncertainty sampling o…
Lightweight Uncertainty Quantification with Simplex Semantic Segmentation for Terrain Traversability
Judith Dijk, Gertjan Burghouts, Kapil D. Katyal +5
For navigation of robots, image segmentation is an important component to determining a terrain's traversability. For safe and efficient navigation, it is key to assess the uncerta…
WiCV 2022: The Tenth Women In Computer Vision Workshop
Doris Antensteiner, Silvia Bucci, Arushi Goel +6
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2022, organized alongside the hybrid CVPR 2022 in New Orleans, Louisiana. It provides a voice to a…
Maximum Class Separation as Inductive Bias in One Matrix
Tejaswi Kasarla, Gertjan J. Burghouts, Max van Spengler +3
Maximizing the separation between classes constitutes a well-known inductive bias in machine learning and a pillar of many traditional algorithms. By default, deep networks are not…
WiCV 2021: The Eighth Women In Computer Vision Workshop
Arushi Goel, Niveditha Kalavakonda, Nour Karessli +5
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2021, organized alongside the virtual CVPR 2021. It provides a voice to a minority (female) group…