978 citations · 4.5k across the 70 of their papers we have counts for
11 papers · 2 filters
Are Large-scale Datasets Necessary for Self-Supervised Pre-training?
Alaaeldin El-Nouby, Gautier Izacard, Hugo Touvron +3
Pre-training models on large scale datasets, like ImageNet, is a standard practice in computer vision. This paradigm is especially effective for tasks with small training sets, for…
Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videos
Zongmian Li, Jiri Sedlar, Justin Carpentier +3
In this paper, we introduce a method to automatically reconstruct the 3D motion of a person interacting with an object from a single RGB video. Our method estimates the 3D poses of…
Differentiable Rendering with Perturbed Optimizers
Quentin Le Lidec, Ivan Laptev, Cordelia Schmid +1
Reasoning about 3D scenes from their 2D image projections is one of the core problems in computer vision. Solutions to this inverse and ill-posed problem typically involve a search…
History Aware Multimodal Transformer for Vision-and-Language Navigation
Shizhe Chen, Pierre-Louis Guhur, Cordelia Schmid +1
Vision-and-language navigation (VLN) aims to build autonomous visual agents that follow instructions and navigate in real scenes. To remember previously visited locations and actio…
Reconstructing and grounding narrated instructional videos in 3D
Dimitri Zhukov, Ignacio Rocco, Ivan Laptev +4
Narrated instructional videos often show and describe manipulations of similar objects, e.g., repairing a particular model of a car or laptop. In this work we aim to reconstruct su…
Airbert: In-domain Pretraining for Vision-and-Language Navigation
Pierre-Louis Guhur, Makarand Tapaswi, Shizhe Chen +2
Vision-and-language navigation (VLN) aims to enable embodied agents to navigate in realistic environments using natural language instructions. Given the scarcity of domain-specific…
Towards unconstrained joint hand-object reconstruction from RGB videos
Yana Hasson, Gül Varol, Ivan Laptev +1
Our work aims to obtain 3D reconstruction of hands and manipulated objects from monocular videos. Reconstructing hand-object manipulations holds a great potential for robotics and…
XCiT: Cross-Covariance Image Transformers
Alaaeldin El-Nouby, Hugo Touvron, Mathilde Caron +8
Following their success in natural language processing, transformers have recently shown much promise for computer vision. The self-attention operation underlying transformers yiel…
Segmenter: Transformer for Semantic Segmentation
Robin Strudel, Ricardo Garcia, Ivan Laptev +1
Image segmentation is often ambiguous at the level of individual image patches and requires contextual information to reach label consensus. In this paper we introduce Segmenter, a…
Thinking Fast and Slow: Efficient Text-to-Visual Retrieval with Transformers
Antoine Miech, Jean-Baptiste Alayrac, Ivan Laptev +2
Our objective is language-based search of large-scale image and video datasets. For this task, the approach that consists of independently mapping text and vision to a joint embedd…
Training Vision Transformers for Image Retrieval
Alaaeldin El-Nouby, Natalia Neverova, Ivan Laptev +1
Transformers have shown outstanding results for natural language understanding and, more recently, for image classification. We here extend this work and propose a transformer-base…